Data processing systems and communication systems and methods for the efficient generation of privacy risk assessments

ABSTRACT

Data processing computer systems, in various embodiments, are adapted for: (1) presenting a threshold privacy assessment that includes a first set of privacy-related questions for a privacy campaign (2) receiving respective answers to the first set of questions; (3) using this initial set of answers to calculate an initial privacy risk score for the privacy campaign; (4) determining whether the privacy risk score exceeds the threshold privacy risk value; (5) in response to the privacy risk score exceeding the threshold privacy risk value, providing one or more supplemental questions to the user to facilitate the completion of a full privacy impact assessment. In some embodiments, in response to determining that the privacy risk score does not exceed the threshold privacy risk value, the systems and methods provide an indication that the particular privacy campaign is a relatively low privacy campaign.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 15/256,419, filed Sep. 2, 2016, which is a continuation of U.S.patent application Ser. No. 15/169,643, filed May 31, 2016, which claimspriority to U.S. Provisional Patent Application Ser. No. 62/317,457,filed Apr. 1, 2016, and this application also claims priority to U.S.Provisional Patent Application Ser. No. 62/360,123, filed Jul. 8, 2016;U.S. Provisional Patent Application Ser. No. 62/353,802, filed Jun. 23,2016; and U.S. Provisional Patent Application Ser. No. 62/348,695, filedJun. 10, 2016, the disclosures of which are hereby incorporated byreference in their entirety.

TECHNICAL FIELD

This disclosure relates to a data processing system and methods forretrieving data regarding a plurality of privacy campaigns, and forusing that data to assess a relative risk associated with the dataprivacy campaign, provide an audit schedule for each campaign, andelectronically display campaign information.

BACKGROUND

Over the past years, privacy and security policies, and relatedoperations have become increasingly important. Breaches in security,leading to the unauthorized access of personal data (which may includesensitive personal data) have become more frequent among companies andother organizations of all sizes. Such personal data may include, but isnot limited to, personally identifiable information (PII), which may beinformation that directly (or indirectly) identifies an individual orentity. Examples of PII include names, addresses, dates of birth, socialsecurity numbers, and biometric identifiers such as a person'sfingerprints or picture. Other personal data may include, for example,customers' Internet browsing habits, purchase history, or even theirpreferences (i.e., likes and dislikes, as provided or obtained throughsocial media). While not all personal data may be sensitive, in thewrong hands, this kind of information may have a negative impact on theindividuals or entities whose sensitive personal data is collected,including identity theft and embarrassment. Not only would this breachhave the potential of exposing individuals to malicious wrongdoing, thefallout from such breaches may result in damage to reputation, potentialliability, and costly remedial action for the organizations thatcollected the information and that were under an obligation to maintainits confidentiality and security. These breaches may result in not onlyfinancial loss, but loss of credibility, confidence, and trust fromindividuals, stakeholders, and the public.

Many organizations that obtain, use, and transfer personal data,including sensitive personal data, have begun to address these privacyand security issues. To manage personal data, many companies haveattempted to implement operational policies and processes that complywith legal requirements, such as Canada's Personal InformationProtection and Electronic Documents Act (PIPEDA) or the U.S.'s HealthInsurance Portability and Accountability Act (HIPPA) protecting apatient's medical information. The European Union's General DataProtection Regulation (GDPR) can fine companies up to 4% of their globalworldwide turnover (revenue) for not complying with its regulations(companies must comply by March 2018). These operational policies andprocesses also strive to comply with industry best practices (e.g., theDigital Advertising Alliance's Self-Regulatory Principles for OnlineBehavioral Advertising). Many regulators recommend conducting privacyimpact assessments, or data protection risk assessments along with datainventory mapping. For example, the GDPR requires data protection impactassessments. Additionally, the United Kingdom ICO's office providesguidance around privacy impact assessments. The OPC in Canada recommendspersonal information inventory, and the Singapore PDPA specificallymentions personal data inventory mapping.

Thus, developing operational policies and processes may reassure notonly regulators, but also an organization's customers, vendors, andother business partners.

For many companies handling personal data, privacy audits, whether doneaccording to AICPA Generally Accepted Privacy Principles, or ISACA's ITStandards, Guidelines, and Tools and Techniques for Audit Assurance andControl Professionals, are not just a best practice, they are arequirement (for example, Facebook and Google will be required toperform 10 privacy audits each until 2032 to ensure that their treatmentof personal data comports with the expectations of the Federal TradeCommission). When the time comes to perform a privacy audit, be it acompliance audit or adequacy audit, the lack of transparency or clarityinto where personal data comes from, where is it stored, who is usingit, where it has been transferred, and for what purpose is it beingused, may bog down any privacy audit process. Even worse, after a breachoccurs and is discovered, many organizations are unable to even identifya clear-cut organizational owner responsible for the breach recovery, orprovide sufficient evidence that privacy policies and regulations werecomplied with.

In light of the above, there is currently a need for improved systemsand methods for monitoring compliance with corporate privacy policiesand applicable privacy laws. Further, there is a need to subjectparticular privacy campaigns to a more detailed analysis based onanswers that are provided in response to a first set of inquiriesregarding the privacy campaign.

SUMMARY

A computer-implemented data processing method, according to variousembodiments, for efficiently conducting privacy risk assessments for aplurality of privacy campaigns comprises, for each of the plurality ofprivacy campaigns: (1) presenting, by one or more processors, athreshold privacy assessment to a user that includes a first set of oneor more questions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of a particular privacycampaign; (2) receiving, by one or more processors, respective answersfor the first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign; (3)determining, by one or more processors, a privacy risk score for theparticular privacy campaign that identifies a level of risk for one ormore of the privacy characteristics indicated in the question/answerpairings; (4) comparing, by one or more processors, the privacy riskscore to a threshold privacy risk value, the threshold privacy riskvalue indicating a pre-determined level of risk regarding the one ormore privacy characteristics of the particular privacy campaign; (5)determining, by one or more processors, whether the privacy risk scoreexceeds the threshold privacy risk value; (6) in response to determiningthat the privacy risk score exceeds the threshold privacy risk value,providing, by one or more processors, a privacy impact assessment to theuser that includes a second set of questions for a second plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign, the second set ofone or more questions including one or more questions that are differentfrom questions within the first set of one or more questions; and (7) inresponse to determining that the privacy risk score does not exceed thethreshold privacy risk value, storing, by one or more processors, anindication that the particular privacy campaign is a low privacy riskcampaign.

A computer-implemented data processing method, according to certainembodiments, for efficiently conducting privacy risk assessments for aplurality of privacy campaigns comprises, for each of the plurality ofprivacy campaigns: (1) presenting, by one or more processors, athreshold privacy assessment to a user that includes a first set of oneor more questions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of the particular privacycampaign; (2) receiving, by one or more processors, respective answersfor the first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign; (3)determining, by one or more processors, a privacy risk score for theparticular privacy campaign that identifies a level of risk for one ormore of the privacy characteristics indicated in the question/answerpairings; (4) comparing, by one or more processors, the privacy riskscore to a threshold privacy risk value, the threshold privacy riskvalue indicating a pre-determined level of risk regarding the one ormore privacy characteristics of the particular privacy campaign; (5)determining, by one or more processors, whether the privacy risk scoreexceeds the threshold privacy risk value; (6) providing, by one or moreprocessors and to the one or more privacy officers, (a) a firstselection option to initiate a privacy impact assessment to be providedto the user that includes a second set of questions for a secondplurality of question/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign, the second set ofone or more questions includes one or more questions that aresupplemental to the first set of one or more questions and (b) a secondselection option to indicate that the particular privacy campaign is alow privacy risk campaign; (7) in response to receiving an indication ofselection of the first selection option by the one or more privacyofficers, providing, by one or more processors, the full privacy impactassessment to the user; and (8) in response to receiving an indicationof selection of the second selection option by the one or more privacyofficers, storing, by one or more processors, an indication that theparticular privacy campaign is a low privacy risk campaign.

A computer-implemented data processing method, according to particularembodiments, for efficiently conducting privacy risk assessments for aplurality of privacy campaigns comprises, for each of the plurality ofprivacy campaigns: (1) presenting, by one or more processors, athreshold privacy assessment to a user that includes a first set of oneor more questions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of the particular privacycampaign; (2) receiving, by one or more processors, respective answersfor the first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign; (3)determining, by one or more processors, a first privacy risk score forthe particular privacy campaign that identifies a level of risk for oneor more of the privacy characteristics indicated in the first pluralityof question/answer pairings; (4) comparing, by one or more processors,the first privacy risk score to a first threshold privacy risk value,the first threshold privacy risk value indicating a pre-determined levelof risk regarding the one or more privacy characteristics of theparticular privacy campaign; (5) determining, by one or more processors,that the first privacy risk score exceeds the first threshold privacyrisk value; (6) in response to determining that the first privacy riskscore exceeds the first threshold privacy risk value, providing, by oneor more processors, a privacy impact assessment to the user thatincludes a second set of questions for a second plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign, the second set ofone or more questions includes a greater number of questions than thefirst set of one or more questions; (7) receiving, by one or moreprocessors, respective answers for the second plurality ofquestion/answer pairings regarding the one or more privacycharacteristics of the particular privacy campaign; (8) determining, byone or more processors, a second privacy risk score for the particularprivacy campaign that identifies a level of risk for one or more of theprivacy characteristics indicated in the second plurality ofquestion/answer pairings; (9) comparing, by one or more processors, thesecond privacy risk score to a second threshold privacy risk value, thesecond threshold privacy risk value indicating a pre-determined level ofrisk regarding the one or more privacy characteristics of the particularprivacy campaign; (10) determining, by one or more processors, whetherthe second privacy risk score exceeds the second threshold privacy riskvalue; (11) in response to determining that the second privacy riskscore exceeds the second threshold privacy risk value, providing, by oneor more processors, an advanced privacy impact assessment to the userthat includes a third set of questions for a third plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign, the third set of oneor more questions includes a greater number of questions than the secondset of one or more questions; and (12) in response to determining thatthe second privacy risk score does not exceed the second thresholdprivacy risk value, storing, by one or more processors, an indicationthat the particular privacy campaign is a low privacy risk campaign.

The details of one or more embodiments of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of a system and method for operationalizing privacycompliance and assessing risk of privacy campaigns are described below.In the course of this description, reference will be made to theaccompanying drawings, which are not necessarily drawn to scale, andwherein:

FIG. 1 is diagram illustrating an exemplary network environment in whichthe present system and methods for operationalizing privacy compliancemay operate.

FIG. 2 is a schematic diagram of a computer (such as the server 120, oruser device 140, 150, 160, 170, 180, 190) that is suitable for use invarious embodiments;

FIG. 3 is a diagram illustrating an example of the elements (e.g.,subjects, owner, etc.) that may be involved in privacy compliance.

FIG. 4 is a flow chart showing an example of a process performed by theMain Privacy Compliance Module.

FIG. 5 is a flow chart showing an example of a process performed by theRisk Assessment Module.

FIG. 6 is a flow chart showing an example of a process performed by thePrivacy Audit Module.

FIG. 7 is a flow chart showing an example of a process performed by theData Flow Diagram Module.

FIG. 8 is an example of a GUI (Graphical User Interface) showing adialog that allows for entry of description information related to aprivacy campaign.

FIG. 9 is an example of a notification, generated by the system,informing a business representative (e.g., owner) that they have beenassigned to a particular privacy campaign.

FIG. 10 is an example of a GUI showing a dialog that allows entry of thetype of personal data that is being collected for a campaign.

FIG. 11 is an example of a GUI that shows a dialog that allowscollection of campaign data regarding the subject from whom the personaldata was collected.

FIG. 12 is an example of a GUI that shows a dialog for inputtinginformation regarding where the personal data related to a campaign isstored.

FIG. 13 is an example of a GUI that shows information regarding theaccess of the personal data related to a campaign.

FIG. 14 is an example of an instant messaging session overlaid on top ofa GUI, wherein the GUI contains prompts for the entry or selection ofcampaign data.

FIG. 15 is an example of a GUI showing an inventory page.

FIG. 16 is an example of a GUI showing campaign data, including a dataflow diagram.

FIG. 17 is an example of a GUI showing a page that allows editing ofcampaign data.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings. It should be understood that theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein. Rather, theseembodiments are provided so that this disclosure will be thorough andcomplete, and will fully convey the scope of the invention to thoseskilled in the art. Like numbers refer to like elements throughout.

Overview

According to exemplary embodiments, a system for operationalizingprivacy compliance is described herein. The system may be comprised ofone or more servers and client computing devices that execute softwaremodules that facilitate various functions.

A Main Privacy Compliance Module is operable to allow a user to initiatethe creation of a privacy campaign (i.e., a business function, system,product, technology, process, project, engagement, initiative, campaign,etc., that may utilize personal data collected from one or more personsor entities). The personal data may contain PII that may be sensitivepersonal data. The user can input information such as the name anddescription of the campaign. The user may also select whether he/shewill take ownership of the campaign (i.e., be responsible for providingthe information needed to create the campaign and oversee the conductingof privacy audits related to the campaign), or assign the campaign toone or more other persons. The Main Privacy Compliance Module cangenerate a sequence or serious of GUI windows that facilitate the entryof campaign data representative of attributes related to the privacycampaign (e.g., attributes that might relate to the description of thepersonal data, what personal data is collected, whom the data iscollected from, the storage of the data, and access to that data).

Based on the information input, a Risk Assessment Module may be operableto take into account Weighting Factors and Relative Risk Ratingsassociated with the campaign in order to calculate a numerical RiskLevel associated with the campaign, as well as an Overall RiskAssessment for the campaign (i.e., low-risk, medium risk, or high risk).The Risk Level may be indicative of the likelihood of a breach involvingpersonal data related to the campaign being compromised (i.e., lost,stolen, accessed without authorization, inadvertently disclosed,maliciously disclosed, etc.). An inventory page can visually depict theRisk Level for one or more privacy campaigns.

After the Risk Assessment Module has determined a Risk Level for acampaign, a Privacy Audit Module may be operable to use the Risk Levelto determine an audit schedule for the campaign. The audit schedule maybe editable, and the Privacy Audit Module also facilitates the privacyaudit process by sending alerts when a privacy audit is impending, orsending alerts when a privacy audit is overdue.

The system may also include a Data Flow Diagram Module for generating adata flow diagram associated with a campaign. An exemplary data flowdiagram displays one or more shapes representing the source from whichdata associated with the campaign is derived, the destination (orlocation) of that data, and which departments or software systems mayhave access to the data. The Data Flow Diagram Module may also generateone or more security indicators for display. The indicators may include,for example, an “eye” icon to indicate that the data is confidential, a“lock” icon to indicate that the data, and/or a particular flow of data,is encrypted, or an “unlocked lock” icon to indicate that the data,and/or a particular flow of data, is not encrypted. Data flow lines maybe colored differently to indicate whether the data flow is encrypted orunencrypted.

The system also provides for a Communications Module that facilitatesthe creation and transmission of notifications and alerts (e.g., viaemail). The Communications Module may also instantiate an instantmessaging session and overlay the instant messaging session over one ormore portions of a GUI in which a user is presented with prompts toenter or select information.

Exemplary Technical Platforms

As will be appreciated by one skilled in the relevant field, a systemfor operationalizing privacy compliance and assessing risk of privacycampaigns may be, for example, embodied as a computer system, a method,or a computer program product. Accordingly, various embodiments may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, or an embodiment combining software and hardware aspects.Furthermore, particular embodiments may take the form of a computerprogram product stored on a computer-readable storage medium havingcomputer-readable instructions (e.g., software) embodied in the storagemedium. Various embodiments may take the form of web, mobile, wearablecomputer-implemented, computer software. Any suitable computer-readablestorage medium may be utilized including, for example, hard disks,compact disks, DVDs, optical storage devices, and/or magnetic storagedevices.

Various embodiments are described below with reference to block diagramsand flowchart illustrations of methods, apparatuses (e.g., systems) andcomputer program products. It should be understood that each step of theblock diagrams and flowchart illustrations, and combinations of steps inthe block diagrams and flowchart illustrations, respectively, may beimplemented by a computer executing computer program instructions. Thesecomputer program instructions may be loaded onto a general-purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructionswhich execute on the computer or other programmable data processingapparatus to create means for implementing the functions specified inthe flowchart step or steps

These computer program instructions may also be stored in acomputer-readable memory that may direct a computer or otherprogrammable data processing apparatus to function in a particularmanner such that the instructions stored in the computer-readable memoryproduce an article of manufacture that is configured for implementingthe function specified in the flowchart step or steps. The computerprogram instructions may also be loaded onto a computer or otherprogrammable data processing apparatus to cause a series of operationalsteps to be performed on the computer or other programmable apparatus toproduce a computer implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide stepsfor implementing the functions specified in the flowchart step or steps.

Accordingly, steps of the block diagrams and flowchart illustrationssupport combinations of mechanisms for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instructions for performing the specified functions. Itshould also be understood that each step of the block diagrams andflowchart illustrations, and combinations of steps in the block diagramsand flowchart illustrations, may be implemented by special purposehardware-based computer systems that perform the specified functions orsteps, or combinations of special purpose hardware and other hardwareexecuting appropriate computer instructions.

Example System Architecture

FIG. 1 is a block diagram of a System 100 according to a particularembodiment. As may be understood from this figure, the System 100includes one or more computer networks 110, a Server 120, a StorageDevice 130 (which may contain one or more databases of information), oneor more remote client computing devices such as a tablet computer 140, adesktop or laptop computer 150, or a handheld computing device 160, suchas a cellular phone, browser and Internet capable set-top boxes 170connected with a TV 180, or even smart TVs 180 having browser andInternet capability. The client computing devices attached to thenetwork may also include copiers/printers 190 having hard drives (asecurity risk since copies/prints may be stored on these hard drives).The Server 120, client computing devices, and Storage Device 130 may bephysically located in a central location, such as the headquarters ofthe organization, for example, or in separate facilities. The devicesmay be owned or maintained by employees, contractors, or other thirdparties (e.g., a cloud service provider). In particular embodiments, theone or more computer networks 115 facilitate communication between theServer 120, one or more client computing devices 140, 150, 160, 170,180, 190, and Storage Device 130.

The one or more computer networks 115 may include any of a variety oftypes of wired or wireless computer networks such as the Internet, aprivate intranet, a public switched telephone network (PSTN), or anyother type of network. The communication link between the Server 120,one or more client computing devices 140, 150, 160, 170, 180, 190, andStorage Device 130 may be, for example, implemented via a Local AreaNetwork (LAN) or via the Internet.

Example Computer Architecture Used within the System

FIG. 2 illustrates a diagrammatic representation of the architecture ofa computer 200 that may be used within the System 100, for example, as aclient computer (e.g., one of computing devices 140, 150, 160, 170, 180,190, shown in FIG. 1), or as a server computer (e.g., Server 120 shownin FIG. 1). In exemplary embodiments, the computer 200 may be suitablefor use as a computer within the context of the System 100 that isconfigured to operationalize privacy compliance and assess risk ofprivacy campaigns. In particular embodiments, the computer 200 may beconnected (e.g., networked) to other computers in a LAN, an intranet, anextranet, and/or the Internet. As noted above, the computer 200 mayoperate in the capacity of a server or a client computer in aclient-server network environment, or as a peer computer in apeer-to-peer (or distributed) network environment. The computer 200 maybe a personal computer (PC), a tablet PC, a set-top box (STB), aPersonal Digital Assistant (PDA), a cellular telephone, a web appliance,a server, a network router, a switch or bridge, or any other computercapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that computer. Further, while only asingle computer is illustrated, the term “computer” shall also be takento include any collection of computers that individually or jointlyexecute a set (or multiple sets) of instructions to perform any one ormore of the methodologies discussed herein.

An exemplary computer 200 includes a processing device 202, a mainmemory 204 (e.g., read-only memory (ROM), flash memory, dynamicrandom-access memory (DRAM) such as synchronous DRAM (SDRAM) or RambusDRAM (RDRAM), etc.), a static memory 206 (e.g., flash memory, staticrandom-access memory (SRAM), etc.), and a data storage device 218, whichcommunicate with each other via a bus 232.

The processing device 202 represents one or more general-purposeprocessing devices such as a microprocessor, a central processing unit,or the like. More particularly, the processing device 202 may be acomplex instruction set computing (CISC) microprocessor, reducedinstruction set computing (RISC) microprocessor, very long instructionword (VLIW) microprocessor, or processor implementing other instructionsets, or processors implementing a combination of instruction sets. Theprocessing device 202 may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like. The processing device 202 may beconfigured to execute processing logic 226 for performing variousoperations and steps discussed herein.

The computer 200 may further include a network interface device 208. Thecomputer 200 also may include a video display unit 210 (e.g., a liquidcrystal display (LCD) or a cathode ray tube (CRT)), an alphanumericinput device 212 (e.g., a keyboard), a cursor control device 214 (e.g.,a mouse), and a signal generation device 216 (e.g., a speaker). The datastorage device 218 may include a non-transitory computer-readablestorage medium 230 (also known as a non-transitory computer-readablestorage medium or a non-transitory computer-readable medium) on which isstored one or more sets of instructions 222 (e.g., software, softwaremodules) embodying any one or more of the methodologies or functionsdescribed herein. The software 222 may also reside, completely or atleast partially, within main memory 204 and/or within processing device202 during execution thereof by computer 200—main memory 204 andprocessing device 202 also constituting computer-accessible storagemedia. The software 222 may further be transmitted or received over anetwork 220 via network interface device 208.

While the computer-readable storage medium 230 is shown in an exemplaryembodiment to be a single medium, the terms “computer-readable storagemedium” and “machine-accessible storage medium” should be understood toinclude a single medium or multiple media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storethe one or more sets of instructions. The term “computer-readablestorage medium” should also be understood to include any medium that iscapable of storing, encoding or carrying a set of instructions forexecution by the computer and that cause the computer to perform any oneor more of the methodologies of the present invention. The term“computer-readable storage medium” should accordingly be understood toinclude, but not be limited to, solid-state memories, optical andmagnetic media, etc.

Exemplary System Platform

According to various embodiments, the processes and logic flowsdescribed in this specification may be performed by a system (e.g.,System 100) that includes, but is not limited to, one or moreprogrammable processors (e.g., processor 202) executing one or morecomputer program modules to perform functions by operating on input dataand generating output, thereby tying the process to a particular machine(e.g., a machine programmed to perform the processes described herein).This includes processors located in one or more of client computers(e.g., client computers 140, 150, 160, 170, 180, 190 of FIG. 1). Thesedevices connected to network 110 may access and execute one or moreInternet browser-based program modules that are “served up” through thenetwork 110 by one or more servers (e.g., server 120 of FIG. 1), and thedata associated with the program may be stored on a one or more storagedevices, which may reside within a server or computing device (e.g.,Main Memory 204, Static Memory 206), be attached as a peripheral storagedevice to the one or more servers or computing devices, or attached tothe network (e.g., Storage 130).

The System 100 facilitates the acquisition, storage, maintenance, use,and retention of campaign data associated with a plurality of privacycampaigns within an organization. In doing so, various aspects of theSystem 100 initiates and creates a plurality of individual data privacycampaign records that are associated with a variety of privacy-relatedattributes and assessment related meta-data for each campaign. Thesedata elements may include: the subjects of the sensitive information,the respective person or entity responsible for each campaign (e.g., thecampaign's “owner”), the location where the personal data will bestored, the entity or entities that will access the data, the parametersaccording to which the personal data will be used and retained, the RiskLevel associated with a particular campaign (as well as assessments fromwhich the Risk Level is calculated), an audit schedule, and otherattributes and meta-data. The System 100 may also be adapted tofacilitate the setup and auditing of each privacy campaign. Thesemodules may include, for example, a Main Privacy Compliance Module, aRisk Assessment Module, a Privacy Audit Module, a Data Flow DiagramModule, and a Communications Module (examples of which are describedbelow). It is to be understood that these are examples of modules ofvarious embodiments, but the functionalities performed by each module asdescribed may be performed by more (or less) modules. Further, thefunctionalities described as being performed by one module may beperformed by one or more other modules.

A. Example Elements Related to Privacy Campaigns

FIG. 3 provides a high-level visual overview of example “subjects” forparticular data privacy campaigns, exemplary campaign “owners,” variouselements related to the storage and access of personal data, andelements related to the use and retention of the personal data. Each ofthese elements may, in various embodiments, be accounted for by theSystem 100 as it facilitates the implementation of an organization'sprivacy compliance policy.

As may be understood from FIG. 3, sensitive information may be collectedby an organization from one or more subjects 300. Subjects may includecustomers whose information has been obtained by the organization. Forexample, if the organization is selling goods to a customer, theorganization may have been provided with a customer's credit card orbanking information (e.g., account number, bank routing number), socialsecurity number, or other sensitive information.

An organization may also possess personal data originating from one ormore of its business partners. Examples of business partners are vendorsthat may be data controllers or data processors (which have differentlegal obligations under EU data protection laws). Vendors may supply acomponent or raw material to the organization, or an outside contractorresponsible for the marketing or legal work of the organization. Thepersonal data acquired from the partner may be that of the partners, oreven that of other entities collected by the partners. For example, amarketing agency may collect personal data on behalf of theorganization, and transfer that information to the organization.Moreover, the organization may share personal data with one of itspartners. For example, the organization may provide a marketing agencywith the personal data of its customers so that it may conduct furtherresearch.

Other subjects 300 include the organization's own employees.Organizations with employees often collect personal data from theiremployees, including address and social security information, usuallyfor payroll purposes, or even prior to employment, for conducting creditchecks. The subjects 300 may also include minors. It is noted thatvarious corporate privacy policies or privacy laws may require thatorganizations take additional steps to protect the sensitive privacy ofminors.

Still referring to FIG. 3, within an organization, a particularindividual (or groups of individuals) may be designated to be an “owner”of a particular campaign to obtain and manage personal data. Theseowners 310 may have any suitable role within the organization. Invarious embodiments, an owner of a particular campaign will have primaryresponsibility for the campaign, and will serve as a resident expertregarding the personal data obtained through the campaign, and the waythat the data is obtained, stored, and accessed. As shown in FIG. 3, anowner may be a member of any suitable department, including theorganization's marketing, HR, R&D, or IT department. As will bedescribed below, in exemplary embodiments, the owner can always bechanged, and owners can sub-assign other owners (and othercollaborators) to individual sections of campaign data input andoperations.

Referring still to FIG. 3, the system may be configured to account forthe use and retention 315 of personal data obtained in each particularcampaign. The use and retention of personal data may include how thedata is analyzed and used within the organization's operations, whetherthe data is backed up, and which parties within the organization aresupporting the campaign.

The system may also be configured to help manage the storage and access320 of personal data. As shown in FIG. 3, a variety of different partiesmay access the data, and the data may be stored in any of a variety ofdifferent locations, including on-site, or in “the cloud”, i.e., onremote servers that are accessed via the Internet or other suitablenetwork.

B. Main Compliance Module

FIG. 4 illustrates an exemplary process for operationalizing privacycompliance. Main Privacy Compliance Module 400, which may be executed byone or more computing devices of System 100, may perform this process.In exemplary embodiments, a server (e.g., server 140) in conjunctionwith a client computing device having a browser, execute the MainPrivacy Compliance Module (e.g., computing devices 140, 150, 160, 170,180, 190) through a network (network 110). In various exemplaryembodiments, the Main Privacy Compliance Module 400 may call upon othermodules to perform certain functions. In exemplary embodiments, thesoftware may also be organized as a single module to perform variouscomputer executable routines.

I. Adding a Campaign

The process 400 may begin at step 405, wherein the Main PrivacyCompliance Module 400 of the System 100 receives a command to add aprivacy campaign. In exemplary embodiments, the user selects anon-screen button (e.g., the Add Data Flow button 1555 of FIG. 15) thatthe Main Privacy Compliance Module 400 displays on a landing page, whichmay be displayed in a graphical user interface (GUI), such as a window,dialog box, or the like. The landing page may be, for example, theinventory page 1500 below. The inventory page 1500 may display a list ofone or more privacy campaigns that have already been input into theSystem 100. As mentioned above, a privacy campaign may represent, forexample, a business operation that the organization is engaged in, orsome business record, that may require the use of personal data, whichmay include the personal data of a customer or some other entity.Examples of campaigns might include, for example, Internet UsageHistory, Customer Payment Information, Call History Log, CellularRoaming Records, etc. For the campaign “Internet Usage History,” amarketing department may need customers' on-line browsing patterns torun analytics. This might entail retrieving and storing customers' IPaddresses, MAC address, URL history, subscriber ID, and otherinformation that may be considered personal data (and even sensitivepersonal data). As will be described herein, the System 100, through theuse of one or more modules, including the Main Privacy Campaign Module400, creates a record for each campaign. Data elements of campaign datamay be associated with each campaign record that represents attributessuch as: the type of personal data associated with the campaign; thesubjects having access to the personal data; the person or personswithin the company that take ownership (e.g., business owner) forensuring privacy compliance for the personal data associated with eachcampaign; the location of the personal data; the entities having accessto the data; the various computer systems and software applications thatuse the personal data; and the Risk Level (see below) associated withthe campaign.

II. Entry of Privacy Campaign Related Information, Including Owner

At step 410, in response to the receipt of the user's command to add aprivacy campaign record, the Main Privacy Compliance Module 400initiates a routine to create an electronic record for a privacycampaign, and a routine for the entry data inputs of information relatedto the privacy campaign. The Main Privacy Compliance Module 400 maygenerate one or more graphical user interfaces (e.g., windows, dialogpages, etc.), which may be presented one GUI at a time. Each GUI mayshow prompts, editable entry fields, check boxes, radial selectors,etc., where a user may enter or select privacy campaign data. Inexemplary embodiments, the Main Privacy Compliance Module 400 displayson the graphical user interface a prompt to create an electronic recordfor the privacy campaign. A user may choose to add a campaign, in whichcase the Main Privacy Compliance Module 400 receives a command to createthe electronic record for the privacy campaign, and in response to thecommand, creates a record for the campaign and digitally stores therecord for the campaign. The record for the campaign may be stored in,for example, storage 130, or a storage device associated with the MainPrivacy Compliance Module (e.g., a hard drive residing on Server 110, ora peripheral hard drive attached to Server 110).

The user may be a person who works in the Chief Privacy Officer'sorganization (e.g., a privacy office rep, or privacy officer). Theprivacy officer may be the user that creates the campaign record, andenters initial portions of campaign data (e.g., “high level” datarelated to the campaign), for example, a name for the privacy campaign,a description of the campaign, and a business group responsible foradministering the privacy operations related to that campaign (forexample, though the GUI shown in FIG. 6). The Main Privacy ComplianceModule 400 may also prompt the user to enter a person or entityresponsible for each campaign (e.g., the campaign's “owner”). The ownermay be tasked with the responsibility for ensuring or attempting toensure that the privacy policies or privacy laws associated withpersonal data related to a particular privacy campaign are beingcomplied with. In exemplary embodiments, the default owner of thecampaign may be the person who initiated the creation of the privacycampaign. That owner may be a person who works in the Chief PrivacyOfficer's organization (e.g., a privacy office rep, or privacy officer).The initial owner of the campaign may designate someone else to be theowner of the campaign. The designee may be, for example, arepresentative of some business unit within the organization (a businessrep). Additionally, more than one owner may be assigned. For example,the user may assign a primary business rep, and may also assign aprivacy office rep as owners of the campaign.

In many instances, some or most of the required information related tothe privacy campaign record might not be within the knowledge of thedefault owner (i.e., the privacy office rep). The Main Data ComplianceModule 400 can be operable to allow the creator of the campaign record(e.g., a privacy officer rep) to designate one or more othercollaborators to provide at least one of the data inputs for thecampaign data. Different collaborators, which may include the one ormore owners, may be assigned to different questions, or to specificquestions within the context of the privacy campaign. Additionally,different collaborators may be designated to respond to pats ofquestions. Thus, portions of campaign data may be assigned to differentindividuals.

Still referring to FIG. 4, if at step 415 the Main Privacy ComplianceModule 400 has received an input from a user to designate a new ownerfor the privacy campaign that was created, then at step 420, the MainPrivacy Compliance Module 400 may notify that individual via a suitablenotification that the privacy campaign has been assigned to him or her.Prior to notification, the Main Privacy Compliance Module 400 maydisplay a field that allows the creator of the campaign to add apersonalized message to the newly assigned owner of the campaign to beincluded with that notification. In exemplary embodiments, thenotification may be in the form of an email message. The email mayinclude the personalized message from the assignor, a standard messagethat the campaign has been assigned to him/her, the deadline forcompleting the campaign entry, and instructions to log in to the systemto complete the privacy campaign entry (along with a hyperlink thattakes the user to a GUI providing access to the Main Privacy ComplianceModule 400. Also included may be an option to reply to the email if anassigned owner has any questions, or a button that when clicked on,opens up a chat window (i.e., instant messenger window) to allow thenewly assigned owner and the assignor a GUI in which they are able tocommunicate in real-time. An example of such a notification appears inFIG. 16 below. In addition to owners, collaborators that are assigned toinput portions of campaign data may also be notified through similarprocesses. In exemplary embodiments, The Main Privacy Compliance Module400 may, for example through a Communications Module, be operable tosend collaborators emails regarding their assignment of one or moreportions of inputs to campaign data. Or through the CommunicationsModule, selecting the commentators button brings up one or morecollaborators that are on-line (with the off-line users still able tosee the messages when they are back on-line. Alerts indicate that one ormore emails or instant messages await a collaborator.

At step 425, regardless of whether the owner is the user (i.e., thecreator of the campaign), “someone else” assigned by the user, or othercollaborators that may be designated with the task of providing one ormore items of campaign data, the Main Privacy Campaign Module 400 may beoperable to electronically receive campaign data inputs from one or moreusers related to the personal data related to a privacy campaign througha series of displayed computer-generated graphical user interfacesdisplaying a plurality of prompts for the data inputs. In exemplaryembodiments, through a step-by-step process, the Main Privacy CampaignModule may receive from one or more users' data inputs that includecampaign data like: (1) a description of the campaign; (2) one or moretypes of personal data to be collected and stored as part of thecampaign; (3) individuals from which the personal data is to becollected; (4) the storage location of the personal data, and (5)information regarding who will have access to the personal data. Theseinputs may be obtained, for example, through the graphical userinterfaces shown in FIGS. 8 through 13, wherein the Main ComplianceModule 400 presents on sequentially appearing GUIs the prompts for theentry of each of the enumerated campaign data above. The Main ComplianceModule 400 may process the campaign data by electronically associatingthe campaign data with the record for the campaign and digitally storingthe campaign data with the record for the campaign. The campaign datamay be digitally stored as data elements in a database residing in amemory location in the server 120, a peripheral storage device attachedto the server, or one or more storage devices connected to the network(e.g., storage 130). If campaign data inputs have been assigned to oneor more collaborators, but those collaborators have not input the datayet, the Main Compliance Module 400 may, for example through theCommunications Module, sent an electronic message (such as an email)alerting the collaborators and owners that they have not yet suppliedtheir designated portion of campaign data.

III. Privacy Campaign Information Display

At step 430, Main Privacy Compliance Module 400 may, in exemplaryembodiments, call upon a Risk Assessment Module 430 that may determineand assign a Risk Level for the privacy campaign, based wholly or inpart on the information that the owner(s) have input. The RiskAssessment Module 430 will be discussed in more detail below.

At step 432, Main Privacy Compliance Module 400 may in exemplaryembodiments, call upon a Privacy Audit Module 432 that may determine anaudit schedule for each privacy campaign, based, for example, wholly orin part on the campaign data that the owner(s) have input, the RiskLevel assigned to a campaign, and/or any other suitable factors. ThePrivacy Audit Module 432 may also be operable to display the status ofan audit for each privacy campaign. The Privacy Audit Module 432 will bediscussed in more detail below.

At step 435, the Main Privacy Compliance Module 400 may generate anddisplay a GUI showing an inventory page (e.g., inventory page 1500) thatincludes information associated with each campaign. That information mayinclude information input by a user (e.g., one or more owners), orinformation calculated by the Main Privacy Compliance Module 400 orother modules. Such information may include for example, the name of thecampaign, the status of the campaign, the source of the campaign, thestorage location of the personal data related to the campaign, etc. Theinventory page 1500 may also display an indicator representing the RiskLevel (as mentioned, determined for each campaign by the Risk AssessmentModule 430), and audit information related to the campaign that wasdetermined by the Privacy Audit Module (see below). The inventory page1500 may be the landing page displayed to users that access the system.Based on the login information received from the user, the Main PrivacyCompliance Module may determine which campaigns and campaign data theuser is authorized to view, and display only the information that theuser is authorized to view. Also from the inventory page 1500, a usermay add a campaign (discussed above in step 405), view more informationfor a campaign, or edit information related to a campaign (see, e.g.,FIGS. 15, 16, 17).

If other commands from the inventory page are received (e.g., add acampaign, view more information, edit information related to thecampaign), then step 440, 445, and/or 450 may be executed.

At step 440, if a command to view more information has been received ordetected, then at step 445, the Main Privacy Compliance Module 400 maypresent more information about the campaign, for example, on a suitablecampaign information page 1500. At this step, the Main PrivacyCompliance Module 400 may invoke a Data Flow Diagram Module (describedin more detail below). The Data Flow Diagram Module may generate a flowdiagram that shows, for example, visual indicators indicating whetherdata is confidential and/or encrypted (see, e.g., FIG. 1600 below).

At step 450, if the system has received a request to edit a campaign,then, at step 455, the system may display a dialog page that allows auser to edit information regarding the campaign (e.g., edit campaigndialog 1700).

At step 460, if the system has received a request to add a campaign, theprocess may proceed back to step 405.

C. Risk Assessment Module

FIG. 5 illustrates an exemplary process for determining a Risk Level andOverall Risk Assessment for a particular privacy campaign performed byRisk Assessment Module 430.

I. Determining Risk Level

In exemplary embodiments, the Risk Assessment Module 430 may be operableto calculate a Risk Level for a campaign based on the campaign datarelated to the personal data associated with the campaign. The RiskAssessment Module may associate the Risk Level with the record for thecampaign and digitally store the Risk Level with the record for thecampaign.

The Risk Assessment Module 430 may calculate this Risk Level based onany of various factors associated with the campaign. The Risk AssessmentModule 430 may determine a plurality of weighting factors based upon,for example: (1) the nature of the sensitive information collected aspart of the campaign (e.g., campaigns in which medical information,financial information or non-public personal identifying information iscollected may be indicated to be of higher risk than those in which onlypublic information is collected, and thus may be assigned a highernumerical weighting factor); (2) the location in which the informationis stored (e.g., campaigns in which data is stored in the cloud may bedeemed higher risk than campaigns in which the information is storedlocally); (3) the number of individuals who have access to theinformation (e.g., campaigns that permit relatively large numbers ofindividuals to access the personal data may be deemed more risky thanthose that allow only small numbers of individuals to access the data);(4) the length of time that the data will be stored within the system(e.g., campaigns that plan to store and use the personal data over along period of time may be deemed more risky than those that may onlyhold and use the personal data for a short period of time); (5) theindividuals whose sensitive information will be stored (e.g., campaignsthat involve storing and using information of minors may be deemed ofgreater risk than campaigns that involve storing and using theinformation of adults); (6) the country of residence of the individualswhose sensitive information will be stored (e.g., campaigns that involvecollecting data from individuals that live in countries that haverelatively strict privacy laws may be deemed more risky than those thatinvolve collecting data from individuals that live in countries thathave relative lax privacy laws). It should be understood that any othersuitable factors may be used to assess the Risk Level of a particularcampaign, including any new inputs that may need to be added to the riskcalculation.

In particular embodiments, one or more of the individual factors may beweighted (e.g., numerically weighted) according to the deemed relativeimportance of the factor relative to other factors (i.e., Relative RiskRating).

These weightings may be customized from organization to organization,and/or according to different applicable laws. In particularembodiments, the nature of the sensitive information will be weightedhigher than the storage location of the data, or the length of time thatthe data will be stored.

In various embodiments, the system uses a numerical formula to calculatethe Risk Level of a particular campaign. This formula may be, forexample: Risk Level for campaign=(Weighting Factor of Factor1)*(Relative Risk Rating of Factor 1)+(Weighting Factor of Factor2)*(Relative Risk Rating of Factor 2)+(Weighting Factor of FactorN)*(Relative Risk Rating of Factor N). As a simple example, the RiskLevel for a campaign that only collects publicly available informationfor adults and that stores the information locally for a short period ofseveral weeks might be determined as Risk Level=(Weighting Factor ofNature of Sensitive Information)*(Relative Risk Rating of ParticularSensitive Information to be Collected)+(Weighting Factor of Individualsfrom which Information is to be Collected)*(Relative Risk Rating ofIndividuals from which Information is to be Collected)+(Weighting Factorof Duration of Data Retention)*(Relative Risk Rating of Duration of DataRetention)+(Weighting Factor of Individuals from which Data is to beCollected)*(Relative Risk Rating of Individuals from which Data is to beCollected). In this example, the Weighting Factors may range, forexample from 1-5, and the various Relative Risk Ratings of a factor mayrange from 1-10. However, the system may use any other suitable ranges.

In particular embodiments, the Risk Assessment Module 430 may havedefault settings for assigning Overall Risk Assessments to respectivecampaigns based on the numerical Risk Level value determined for thecampaign, for example, as described above. The organization may alsomodify these settings in the Risk Assessment Module 430 by assigning itsown Overall Risk Assessments based on the numerical Risk Level. Forexample, the Risk Assessment Module 430 may, based on default or userassigned settings, designate: (1) campaigns with a Risk Level of 1-7 as“low risk” campaigns, (2) campaigns with a Risk Level of 8-15 as “mediumrisk” campaigns; (3) campaigns with a Risk Level of over 16 as “highrisk” campaigns. As show below, in an example inventory page 1500, theOverall Risk Assessment for each campaign can be indicated by up/downarrow indicators, and further, the arrows may have different shading (orcolor, or portions shaded) based upon this Overall Risk Assessment. Theselected colors may be conducive for viewing by those who suffer fromcolor blindness.

Thus, the Risk Assessment Module 430 may be configured to automaticallycalculate the numerical Risk Level for each campaign within the system,and then use the numerical Risk Level to assign an appropriate OverallRisk Assessment to the respective campaign. For example, a campaign witha Risk Level of 5 may be labeled with an Overall Risk Assessment as “LowRisk”. The system may associate both the Risk Level and the Overall RiskAssessment with the campaign and digitally store them as part of thecampaign record.

II. Exemplary Process for Assessing Risk

Accordingly, as shown in FIG. 5, in exemplary embodiments, the RiskAssessment Module 430 electronically retrieves from a database (e.g.,storage device 130) the campaign data associated with the record for theprivacy campaign. It may retrieve this information serially, or inparallel. At step 505, the Risk Assessment Module 430 retrievesinformation regarding (1) the nature of the sensitive informationcollected as part of the campaign. At step 510, the Risk AssessmentModule 430 retrieves information regarding the (2) the location in whichthe information related to the privacy campaign is stored. At step 515,the Risk Assessment Module 430 retrieves information regarding (3) thenumber of individuals who have access to the information. At step 520,the Risk Assessment Module retrieves information regarding (4) thelength of time that the data associated with a campaign will be storedwithin the System 100. At step 525, the Risk Assessment Module retrievesinformation regarding (5) the individuals whose sensitive informationwill be stored. At step 530, the Risk Assessment Module retrievesinformation regarding (6) the country of residence of the individualswhose sensitive information will be stored.

At step 535, the Risk Assessment Module takes into account any usercustomizations to the weighting factors related to each of the retrievedfactors from steps 505, 510, 515, 520, 525, and 530. At steps 540 and545, the Risk Assessment Module applies either default settings to theweighting factors (which may be based on privacy laws), orcustomizations to the weighting factors. At step 550, the RiskAssessment Module determines a plurality of weighting factors for thecampaign. For example, for the factor related to the nature of thesensitive information collected as part of the campaign, a weightingfactor of 1-5 may be assigned based on whether non-public personalidentifying information is collected.

At step 555, the Risk Assessment Module takes into account any usercustomizations to the Relative Risk assigned to each factor, and at step560 and 565, will either apply default values (which can be based onprivacy laws) or the customized values for the Relative Risk. At step570, the Risk Assessment Module assigns a relative risk rating for eachof the plurality of weighting factors. For example, the relative riskrating for the location of the information of the campaign may beassigned a numerical number (e.g., from 1-10) that is lower than thenumerical number assigned to the Relative Risk Rating for the length oftime that the sensitive information for that campaign is retained.

At step 575, the Risk Assessment Module 430 calculates the relative riskassigned to the campaign based upon the plurality of Weighting Factorsand the Relative Risk Rating for each of the plurality of factors. As anexample, the Risk Assessment Module 430 may make this calculation usingthe formula of Risk Level=(Weighting Factor of Factor 1)*(Relative RiskRating of Factor 1)+(Weighting Factor of Factor 2)*(Relative Risk Ratingof Factor 2)+(Weighting Factor of Factor N)*(Relative Risk Rating ofFactor N).

At step 580, based upon the numerical value derived from step 575, theRisk Assessment Module 430 may determine an Overall Risk Assessment forthe campaign. The Overall Risk Assessment determination may be made forthe privacy campaign may be assigned based on the following criteria,which may be either a default or customized setting: (1) campaigns witha Risk Level of 1-7 as “low risk” campaigns, (2) campaigns with a RiskLevel of 8-15 as “medium risk” campaigns; (3) campaigns with a RiskLevel of over 16 as “high risk” campaigns. The Overall Risk Assessmentis then associated and stored with the campaign record.

D. Privacy Audit Module

The System 100 may determine an audit schedule for each campaign, andindicate, in a particular graphical user interface (e.g., inventory page1500), whether a privacy audit is coming due (or is past due) for eachparticular campaign and, if so, when the audit is/was due. The System100 may also be operable to provide an audit status for each campaign,and alert personnel of upcoming or past due privacy audits. To furtherthe retention of evidence of compliance, the System 100 may also receiveand store evidence of compliance. A Privacy Audit Module 432, mayfacilitate these functions.

I. Determining a Privacy Audit Schedule and Monitoring Compliance

In exemplary embodiments, the Privacy Audit Module 432 is adapted toautomatically schedule audits and manage compliance with the auditschedule. In particular embodiments, the system may allow a user tomanually specify an audit schedule for each respective campaign. ThePrivacy Audit Module 432 may also automatically determine, and save tomemory, an appropriate audit schedule for each respective campaign,which in some circumstances, may be editable by the user.

The Privacy Audit Module 432 may automatically determine the auditschedule based on the determined Risk Level of the campaign. Forexample, all campaigns with a Risk Level less than 10 may have a firstaudit schedule and all campaigns with a Risk Level of 10 or more mayhave a second audit schedule. The Privacy Audit Module may also beoperable determine the audit schedule based on the Overall RiskAssessment for the campaign (e.g., “low risk” campaigns may have a firstpredetermined audit schedule, “medium risk” campaigns may have a secondpredetermined audit schedule, “high risk” campaigns may have a thirdpredetermined audit schedule, etc.).

In particular embodiments, the Privacy Audit Module 432 mayautomatically facilitate and monitor compliance with the determinedaudit schedules for each respective campaign. For example, the systemmay automatically generate one or more reminder emails to the respectiveowners of campaigns as the due date approaches. The system may also beadapted to allow owners of campaigns, or other users, to submit evidenceof completion of an audit (e.g., by for example, submitting screen shotsthat demonstrate that the specified parameters of each campaign arebeing followed). In particular embodiments, the system is configuredfor, in response to receiving sufficient electronic informationdocumenting completion of an audit, resetting the audit schedule (e.g.,scheduling the next audit for the campaign according to a determinedaudit schedule, as determined above).

II. Exemplary Privacy Audit Process

FIG. 6 illustrates an exemplary process performed by a Privacy AuditModule 432 for assigning a privacy audit schedule and facilitating andmanaging compliance for a particular privacy campaign. At step 605, thePrivacy Audit Module 432 retrieves the Risk Level associated with theprivacy campaign. In exemplary embodiments, the Risk Level may be anumerical number, as determined above by the Risk Assessment Module 430.If the organization chooses, the Privacy Audit Module 432 may use theOverall Risk Assessment to determine which audit schedule for thecampaign to assign.

At step 610, based on the Risk Level of the campaign (or the OverallRisk Assessment), or based on any other suitable factor, the PrivacyAudit Module 432 can assign an audit schedule for the campaign. Theaudit schedule may be, for example, a timeframe (i.e., a certain amountof time, such as number of days) until the next privacy audit on thecampaign to be performed by the one or more owners of the campaign. Theaudit schedule may be a default schedule. For example, the Privacy AuditModule can automatically apply an audit schedule of 120 days for anycampaign having Risk Level of 10 and above. These default schedules maybe modifiable. For example, the default audit schedule for campaignshaving a Risk Level of 10 and above can be changed from 120 days to 150days, such that any campaign having a Risk Level of 10 and above isassigned the customized default audit schedule (i.e., 150 days).Depending on privacy laws, default policies, authority overrides, or thepermission level of the user attempting to modify this default, thedefault might not be modifiable.

At step 615, after the audit schedule for a particular campaign hasalready been assigned, the Privacy Audit Module 432 determines if a userinput to modify the audit schedule has been received. If a user input tomodify the audit schedule has been received, then at step 620, thePrivacy Audit Module 432 determines whether the audit schedule for thecampaign is editable (i.e., can be modified). Depending on privacy laws,default policies, authority overrides, or the permission level of theuser attempting to modify the audit schedule, the campaign's auditschedule might not be modifiable.

At step 625, if the audit schedule is modifiable, then the Privacy AuditModule will allow the edit and modify the audit schedule for thecampaign. If at step 620 the Privacy Audit Module determines that theaudit schedule is not modifiable, in some exemplary embodiments, theuser may still request permission to modify the audit schedule. Forexample, the Privacy Audit Module 432 can at step 630 provide anindication that the audit schedule is not editable, but also provide anindication to the user that the user may contact through the system oneor more persons having the authority to grant or deny permission tomodify the audit schedule for the campaign (i.e., administrators) togain permission to edit the field. The Privacy Audit Module 432 maydisplay an on-screen button that, when selected by the user, sends anotification (e.g., an email) to an administrator. The user can thusmake a request to modify the audit schedule for the campaign in thismanner.

At step 635, the Privacy Audit Module may determine whether permissionhas been granted by an administrator to allow a modification to theaudit schedule. It may make this determination based on whether it hasreceived input from an administrator to allow modification of the auditschedule for the campaign. If the administrator has granted permission,the Privacy Audit Module 432 at step 635 may allow the edit of the auditschedule. If at step 640, a denial of permission is received from theadministrator, or if a certain amount of time has passed (which may becustomized or based on a default setting), the Privacy Audit Module 432retains the audit schedule for the campaign by not allowing anymodifications to the schedule, and the process may proceed to step 645.The Privacy Audit Module may also send a reminder to the administratorthat a request to modify the audit schedule for a campaign is pending.

At step 645, the Privacy Audit Module 432 determines whether a thresholdamount of time (e.g., number of days) until the audit has been reached.This threshold may be a default value, or a customized value. If thethreshold amount of time until an audit has been reached, the PrivacyAudit Module 432 may at step 650 generate an electronic alert. The alertcan be a message displayed to the collaborator the next time thecollaborator logs into the system, or the alert can be an electronicmessage sent to one or more collaborators, including the campaignowners. The alert can be, for example, an email, an instant message, atext message, or one or more of these communication modalities. Forexample, the message may state, “This is a notification that a privacyaudit for Campaign Internet Browsing History is scheduled to occur in 90days.” More than one threshold may be assigned, so that the owner of thecampaign receives more than one alert as the scheduled privacy auditdeadline approaches. If the threshold number of days has not beenreached, the Privacy Audit Module 432 will continue to evaluate whetherthe threshold has been reached (i.e., back to step 645).

In exemplary embodiments, after notifying the owner of the campaign ofan impending privacy audit, the Privacy Audit Module may determine atstep 655 whether it has received any indication or confirmation that theprivacy audit has been completed. In example embodiments, the PrivacyAudit Module allows for evidence of completion to be submitted, and ifsufficient, the Privacy Audit Module 432 at step 660 resets the counterfor the audit schedule for the campaign. For example, a privacy auditmay be confirmed upon completion of required electronic forms in whichone or more collaborators verify that their respective portions of theaudit process have been completed. Additionally, users can submitphotos, screen shots, or other documentation that show that theorganization is complying with that user's assigned portion of theprivacy campaign. For example, a database administrator may take ascreen shot showing that all personal data from the privacy campaign isbeing stored in the proper database and submit that to the system todocument compliance with the terms of the campaign.

If at step 655, no indication of completion of the audit has beenreceived, the Privacy Audit Module 432 can determine at step 665 whetheran audit for a campaign is overdue (i.e., expired). If it is notoverdue, the Privacy Audit Module 432 will continue to wait for evidenceof completion (e.g., step 655). If the audit is overdue, the PrivacyAudit Module 432 at step 670 generates an electronic alert (e.g., anemail, instant message, or text message) to the campaign owner(s) orother administrators indicating that the privacy audit is overdue, sothat the organization can take responsive or remedial measures.

In exemplary embodiments, the Privacy Audit Module 432 may also receivean indication that a privacy audit has begun (not shown), so that thestatus of the audit when displayed on inventory page 1500 shows thestatus of the audit as pending. While the audit process is pending, thePrivacy Audit Module 432 may be operable to generate reminders to besent to the campaign owner(s), for example, to remind the owner of thedeadline for completing the audit.

E. Data Flow Diagram Module

The system 110 may be operable to generate a data flow diagram based onthe campaign data entered and stored, for example in the mannerdescribed above.

I. Display of Security Indicators and Other Information

In various embodiments, a Data Flow Diagram Module is operable togenerate a flow diagram for display containing visual representations(e.g., shapes) representative of one or more parts of campaign dataassociated with a privacy campaign, and the flow of that informationfrom a source (e.g., customer), to a destination (e.g., an internetusage database), to which entities and computer systems have access(e.g., customer support, billing systems). Data Flow Diagram Module mayalso generate one or more security indicators for display. Theindicators may include, for example, an “eye” icon to indicate that thedata is confidential, a “lock” icon to indicate that the data, and/or aparticular flow of data, is encrypted, or an “unlocked lock” icon toindicate that the data, and/or a particular flow of data, is notencrypted. In the example shown in FIG. 16, the dotted arrow linesgenerally depict respective flows of data and the locked or unlockedlock symbols indicate whether those data flows are encrypted orunencrypted. The color of dotted lines representing data flows may alsobe colored differently based on whether the data flow is encrypted ornon-encrypted, with colors conducive for viewing by those who sufferfrom color blindness.

II. Exemplary Process Performed by Data Flow Diagram Module

FIG. 7 shows an example process performed by the Data Flow DiagramModule 700. At step 705, the Data Flow Diagram retrieves campaign datarelated to a privacy campaign record. The campaign data may indicate,for example, that the sensitive information related to the privacycampaign contains confidential information, such as the social securitynumbers of a customer.

At step 710, the Data Flow Diagram Module 700 is operable to displayon-screen objects (e.g., shapes) representative of the Source,Destination, and Access, which indicate that information below theheading relates to the source of the personal data, the storagedestination of the personal data, and access related to the personaldata. In addition to campaign data regarding Source, Destination, andAccess, the Data Flow Diagram Module 700 may also account for userdefined attributes related to personal data, which may also be displayedas on-screen objects. The shape may be, for example, a rectangular box(see, e.g., FIG. 16). At step 715, the Data Flow Diagram Module 700 maydisplay a hyperlink label within the on-screen object (e.g., as shown inFIG. 16, the word “Customer” may be a hyperlink displayed within therectangular box) indicative of the source of the personal data, thestorage destination of the personal data, and access related to thepersonal data, under each of the respective headings. When a user hoversover the hyperlinked word, the Data Flow Diagram is operable to displayadditional campaign data relating to the campaign data associated withthe hyperlinked word. The additional information may also be displayedin a pop up, or a new page. For example, FIG. 16 shows that if a userhovers over the words “Customer,” the Data Flow Diagram Module 700displays what customer information is associated with the campaign(e.g., the Subscriber ID, the IP and Mac Addresses associated with theCustomer, and the customer's browsing and usage history). The Data FlowDiagram Module 700 may also generate for display information relating towhether the source of the data includes minors, and whether consent wasgiven by the source to use the sensitive information, as well as themanner of the consent (for example, through an End User LicenseAgreement (EULA)).

At step 720, the Data Flow Diagram Module 700 may display one or moreparameters related to backup and retention of personal data related tothe campaign, including in association with the storage destination ofthe personal data. As an example, Data Flow Diagram 1615 of FIG. 16displays that the information in the Internet Usage database is backedup, and the retention related to that data is Unknown.

At 725, the Data Flow Diagram Module 700 determines, based on thecampaign data associated with the campaign, whether the personal datarelated to each of the hyperlink labels is confidential. At Step 730, ifthe personal data related to each hyperlink label is confidential, theData Flow Diagram Module 700 generates visual indicator indicatingconfidentiality of that data (e.g., an “eye” icon, as show in Data FlowDiagram 1615). If there is no confidential information for that box,then at step 735, no indicators are displayed. While this is an exampleof the generation of indicators for this particular hyperlink, inexemplary embodiments, any user defined campaign data may visualindicators that may be generated for it.

At step 740, the Data Flow Diagram Module 700 determined whether any ofthe data associated with the source, stored in a storage destination,being used by an entity or application, or flowing to one or moreentities or systems (i.e., data flow) associated with the campaign isdesignated as encrypted. If the data is encrypted, then at step 745 theData Flow Diagram Module 700 may generate an indicator that the personaldata is encrypted (e.g., a “lock” icon). If the data is non-encrypted,then at step 750, the Data Flow Diagram Module 700 displays an indicatorto indicate that the data or particular flow of data is not encrypted.(e.g., an “unlocked lock” icon). An example of a data flow diagram isdepicted in FIG. 9. Additionally, the data flow diagram lines may becolored differently to indicate whether the data flow is encrypted orunencrypted, wherein the colors can still be distinguished by acolor-blind person.

F. Communications Module

In exemplary embodiments, a Communications Module of the System 100 mayfacilitate the communications between various owners and personnelrelated to a privacy campaign. The Communications Module may retaincontact information (e.g., emails or instant messaging contactinformation) input by campaign owners and other collaborators. TheCommunications Module can be operable to take a generated notificationor alert (e.g., alert in step 670 generated by Privacy Audit Module 432)and instantiate an email containing the relevant information. Asmentioned above, the Main Privacy Compliance Module 400 may, for examplethrough a communications module, be operable to send collaboratorsemails regarding their assignment of one or more portions of inputs tocampaign data. Or through the communications module, selecting thecommentators button brings up one or more collaborators that are on-line

In exemplary embodiments, the Communications Module can also, inresponse to a user request (e.g., depressing the “comment” button showin FIG. 9, FIG. 10, FIG. 11, FIG. 12, FIG. 13, FIG. 16), instantiate aninstant messaging session and overlay the instant messaging session overone or more portions of a GUI, including a GUI in which a user ispresented with prompts to enter or select information. An example ofthis instant messaging overlay feature orchestrated by theCommunications Module is shown in FIG. 17. While a real-time messagesession may be generated, off-line users may still able to see themessages when they are back on-line.

The Communications Module may facilitate the generation of alerts thatindicate that one or more emails or instant messages await acollaborator.

If campaign data inputs have been assigned to one or more collaborators,but those collaborators have not input the data yet, the CommunicationsModule, may facilitate the sending of an electronic message (such as anemail) alerting the collaborators and owners that they have not yetsupplied their designated portion of campaign data.

Exemplary User Experience

In the exemplary embodiments of the system for operationalizing privacycompliance, adding a campaign (i.e., data flow) comprises gatheringinformation that includes several phases: (1) a description of thecampaign; (2) the personal data to be collected as part of the campaign;(3) who the personal data relates to; (4) where the personal data bestored; and (5) who will have access to the indicated personal data.

A. FIG. 8: Campaign Record Creation and Collaborator Assignment

FIG. 8 illustrates an example of the first phase of informationgathering to add a campaign. In FIG. 8, a description entry dialog 800may have several fillable/editable fields and drop-down selectors. Inthis example, the user may fill out the name of the campaign in theShort Summary (name) field 805, and a description of the campaign in theDescription field 810. The user may enter or select the name of thebusiness group (or groups) that will be accessing personal data for thecampaign in the Business Group field 815. The user may select theprimary business representative responsible for the campaign (i.e., thecampaign's owner), and designate him/herself, or designate someone elseto be that owner by entering that selection through the Someone Elsefield 820. Similarly, the user may designate him/herself as the privacyoffice representative owner for the campaign, or select someone elsefrom the second Someone Else field 825. At any point, a user assigned asthe owner may also assign others the task of selecting or answering anyquestion related to the campaign. The user may also enter one or moretag words associated with the campaign in the Tags field 830. Afterentry, the tag words may be used to search for campaigns, or used tofilter for campaigns (for example, under Filters 845). The user mayassign a due date for completing the campaign entry, and turn remindersfor the campaign on or off. The user may save and continue, or assignand close.

In example embodiments, some of the fields may be filled in by a user,with suggest-as-you-type display of possible field entries (e.g.,Business Group field 815), and/or may include the ability for the userto select items from a drop-down selector (e.g., drop-down selectors 840a, 840 b, 840 c). The system may also allow some fields to stay hiddenor unmodifiable to certain designated viewers or categories of users.For example, the purpose behind a campaign may be hidden from anyone whois not the chief privacy officer of the company, or the retentionschedule may be configured so that it cannot be modified by anyoneoutside of the organization's' legal department.

B. FIG. 9: Collaborator Assignment Notification and Description Entry

Moving to FIG. 9, in example embodiments, if another businessrepresentative (owner), or another privacy office representative hasbeen assigned to the campaign (e.g., John Doe in FIG. 8), the system maysend a notification (e.g., an electronic notification) to the assignedindividual, letting them know that the campaign has been assigned tohim/her. FIG. 9 shows an example notification 900 sent to John Doe thatis in the form of an email message. The email informs him that thecampaign “Internet Usage Tracking” has been assigned to him, andprovides other relevant information, including the deadline forcompleting the campaign entry and instructions to log in to the systemto complete the campaign (data flow) entry (which may be done, forexample, using a suitable “wizard” program). The user that assigned Johnownership of the campaign may also include additional comments 905 to beincluded with the notification 900. Also included may be an option toreply to the email if an assigned owner has any questions.

In this example, if John selects the hyperlink Privacy Portal 910, he isable to access the system, which displays a landing page 915. Thelanding page 915 displays a Getting Started section 920 to familiarizenew owners with the system, and also display an “About This Data Flow”section 930 showing overview information for the campaign.

C. FIG. 10: What Personal Data is Collected

Moving to FIG. 10, after the first phase of campaign addition (i.e.,description entry phase), the system may present the user (who may be asubsequently assigned business representative or privacy officer) with adialog 1000 from which the user may enter in the type of personal databeing collected.

In addition, questions are described generally as transitionalquestions, but the questions may also include one or more smartquestions in which the system is configured to: (1) pose an initialquestion to a user and, (2) in response to the user's answer satisfyingcertain criteria, presenting the user with one or more follow-upquestions. For example, in FIG. 10, if the user responds with a choiceto add personal data, the user may be additionally presented follow-upprompts, for example, the select personal data window overlaying screen800 that includes commonly used selections may include, for example,particular elements of an individual's contact information (e.g., name,address, email address), Financial/Billing Information (e.g., creditcard number, billing address, bank account number), Online Identifiers(e.g., IP Address, device type, MAC Address), Personal Details(Birthdate, Credit Score, Location), or Telecommunication Data (e.g.,Call History, SMS History, Roaming Status). The System 100 is alsooperable to pre-select or automatically populate choices for example,with commonly-used selections 1005, some of the boxes may already bechecked. The user may also use a search/add tool 1010 to search forother selections that are not commonly used and add another selection.Based on the selections made, the user may be presented with moreoptions and fields. For example, if the user selected “Subscriber ID” aspersonal data associated with the campaign, the user may be prompted toadd a collection purpose under the heading Collection Purpose 1015, andthe user may be prompted to provide the business reason why a SubscriberID is being collected under the “Describe Business Need” heading 1020.

D. FIG. 11: Who Personal Data is Collected from

As displayed in the example of FIG. 11, the third phase of adding acampaign may relate to entering and selecting information regarding whothe personal data is gathered from. As noted above, the personal datamay be gathered from, for example, one or more Subjects 100. In theexemplary “Collected From” dialog 1100, a user may be presented withseveral selections in the “Who Is It Collected From” section 1105. Theseselections may include whether the personal data was to be collectedfrom an employee, customer, or other entity. Any entities that are notstored in the system may be added. The selections may also include, forexample, whether the data was collected from a current or prospectivesubject (e.g., a prospective employee may have filled out an employmentapplication with his/her social security number on it). Additionally,the selections may include how consent was given, for example through anend user license agreement (EULA), on-line Opt-in prompt, Impliedconsent, or an indication that the user is not sure. Additionalselections may include whether the personal data was collected from aminor, and where the subject is located.

E. FIG. 12: Where is the Personal Data Stored

FIG. 12 shows an example “Storage Entry” dialog screen 1200, which is agraphical user interface that a user may use to indicate whereparticular sensitive information is to be stored within the system. Fromthis section, a user may specify, in this case for the Internet UsageHistory campaign, the primary destination of the personal data 1220 andhow long the personal data is to be kept 1230. The personal data may behoused by the organization (in this example, an entity called “Acme”) ora third party. The user may specify an application associated with thepersonal data's storage (in this example, ISP Analytics), and may alsospecify the location of computing systems (e.g., servers) that will bestoring the personal data (e.g., a Toronto data center). Otherselections indicate whether the data will be encrypted and/or backed up.

The system also allows the user to select whether the destinationsettings are applicable to all the personal data of the campaign, orjust select data (and if so, which data). In FIG. 12, the user may alsoselect and input options related to the retention of the personal datacollected for the campaign (e.g., How Long Is It Kept 1230). Theretention options may indicate, for example, that the campaign'spersonal data should be deleted after a per-determined period of timehas passed (e.g., on a particular date), or that the campaign's personaldata should be deleted in accordance with the occurrence of one or morespecified events (e.g., in response to the occurrence of a particularevent, or after a specified period of time passes after the occurrenceof a particular event), and the user may also select whether backupsshould be accounted for in any retention schedule. For example, the usermay specify that any backups of the personal data should be deleted (or,alternatively, retained) when the primary copy of the personal data isdeleted.

F. FIG. 13: Who and What Systems have Access to Personal Data

FIG. 13 describes an example Access entry dialog screen 1300. As part ofthe process of adding a campaign or data flow, the user may specify inthe “Who Has Access” section 1305 of the dialog screen 1300. In theexample shown, the Customer Support, Billing, and Government groupswithin the organization are able to access the Internet Usage Historypersonal data collected by the organization. Within each of these accessgroups, the user may select the type of each group, the format in whichthe personal data was provided, and whether the personal data isencrypted. The access level of each group may also be entered. The usermay add additional access groups via the Add Group button 1310.

G. Facilitating Entry of Campaign Data, Including Chat Shown in FIG. 14

As mentioned above, to facilitate the entry of data collected throughthe example GUIs shown in FIGS. 8 through 12, in exemplary embodiments,the system is adapted to allow the owner of a particular campaign (orother user) to assign certain sections of questions, or individualquestions, related to the campaign to contributors other than the owner.This may eliminate the need for the owner to contact other users todetermine information that they don't know and then enter theinformation into the system themselves. Rather, in various embodiments,the system facilitates the entry of the requested information directlyinto the system by the assigned users.

In exemplary embodiments, after the owner assigns a respectiveresponsible party to each question or section of questions that need tobe answered in order to fully populate the data flow, the system mayautomatically contact each user (e.g., via an appropriate electronicmessage) to inform the user that they have been assigned to complete thespecified questions and/or sections of questions, and provide thoseusers with instructions as to how to log into the system to enter thedata. The system may also be adapted to periodically follow up with eachuser with reminders until the user completes the designated tasks. Asdiscussed elsewhere herein, the system may also be adapted to facilitatereal-time text or voice communications between multiple collaborators asthey work together to complete the questions necessary to define thedata flow. Together, these features may reduce the amount of time andeffort needed to complete each data flow.

To further facilitate collaboration, as shown FIG. 14, in exemplaryembodiments, the System 100 is operable to overlay an instant messagingsession over a GUI in which a user is presented with prompts to enter orselect information. In FIG. 14, a communications module is operable tocreate an instant messaging session window 1405 that overlays the Accessentry dialog screen 1400. In exemplary embodiments, the CommunicationsModule, in response to a user request (e.g., depressing the “comment”button show in FIG. 9, FIG. 10, FIG. 11, FIG. 12, FIG. 13, FIG. 16),instantiates an instant messaging session and overlays the instantmessaging session over one or more portions of the GUI.

H: FIG. 15: Campaign Inventory Page

After new campaigns have been added, for example using the exemplaryprocesses explained in regard to FIGS. 8-13, the users of the system mayview their respective campaign or campaigns, depending on whether theyhave access to the campaign. The chief privacy officer, or anotherprivacy office representative, for example, may be the only user thatmay view all campaigns. A listing of all of the campaigns within thesystem may be viewed on, for example, inventory page 1500 (see below).Further details regarding each campaign may be viewed via, for example,campaign information page 1600, which may be accessed by selecting aparticular campaign on the inventory page 1500. And any informationrelated to the campaign may be edited or added through, for example, theedit campaign dialog 1700 screen. Certain fields or information may notbe editable, depending on the particular user's level of access. A usermay also add a new campaign using a suitable user interface, such as thegraphical user interface shown in FIG. 15 or FIG. 16.

In example embodiments, the System 100 (and more particularly, the MainPrivacy Compliance Module 400) may use the history of past entries tosuggest selections for users during campaign creation and entry ofassociated data. As an example, in FIG. 10, if most entries that containthe term “Internet” and have John Doe as the business rep assigned tothe campaign have the items Subscriber ID, IP Address, and MAC Addressselected, then the items that are commonly used may display aspre-selected items the Subscriber ID, IP address, and MAC Address eachtime a campaign is created having Internet in its description and JohnDoe as its business rep.

FIG. 15 describes an example embodiment of an inventory page 1500 thatmay be generated by the Main Privacy Compliance Module 400. Theinventory page 1500 may be represented in a graphical user interface.Each of the graphical user interfaces (e.g., webpages, dialog boxes,etc.) presented in this application may be, in various embodiments, anHTML-based page capable of being displayed on a web browser (e.g.,Firefox, Internet Explorer, Google Chrome, Opera, etc.), or any othercomputer-generated graphical user interface operable to displayinformation, including information having interactive elements (e.g., aniOS, Mac OS, Android, Linux, or Microsoft Windows application). Thewebpage displaying the inventory page 1500 may include typical featuressuch as a scroll-bar, menu items, as well as buttons for minimizing,maximizing, and closing the webpage. The inventory page 1500 may beaccessible to the organization's chief privacy officer, or any other ofthe organization's personnel having the need, and/or permission, to viewpersonal data.

Still referring to FIG. 15, inventory page 1500 may display one or morecampaigns listed in the column heading Data Flow Summary 1505, as wellas other information associated with each campaign, as described herein.Some of the exemplary listed campaigns include Internet Usage History1510, Customer Payment Information, Call History Log, Cellular RoamingRecords, etc. A campaign may represent, for example, a businessoperation that the organization is engaged in may require the use ofpersonal data, which may include the personal data of a customer. In thecampaign Internet Usage History 1510, for example, a marketingdepartment may need customers' on-line browsing patterns to runanalytics. Examples of more information that may be associated with theInternet Usage History 1510 campaign will be presented in FIG. 4 andFIG. 5. In example embodiments, clicking on (i.e., selecting) the columnheading Data Flow Summary 1505 may result in the campaigns being sortedeither alphabetically, or reverse alphabetically.

The inventory page 1500 may also display the status of each campaign, asindicated in column heading Status 1515. Exemplary statuses may include“Pending Review”, which means the campaign has not been approved yet,“Approved,” meaning the data flow associated with that campaign has beenapproved, “Audit Needed,” which may indicate that a privacy audit of thepersonal data associated with the campaign is needed, and “ActionRequired,” meaning that one or more individuals associated with thecampaign must take some kind of action related to the campaign (e.g.,completing missing information, responding to an outstanding message,etc.). In certain embodiments, clicking on (i.e., selecting) the columnheading Status 1515 may result in the campaigns being sorted by status.

The inventory page 1500 of FIG. 15 may list the “source” from which thepersonal data associated with a campaign originated, under the columnheading “Source” 1520. The sources may include one or more of thesubjects 100 in example FIG. 1. As an example, the campaign “InternetUsage History” 1510 may include a customer's IP address or MAC address.For the example campaign “Employee Reference Checks”, the source may bea particular employee. In example embodiments, clicking on (i.e.,selecting) the column heading Source 1520 may result in the campaignsbeing sorted by source.

The inventory page 1500 of FIG. 15 may also list the “destination” ofthe personal data associated with a particular campaign under the columnheading Destination 1525. Personal data may be stored in any of avariety of places, for example on one or more storage devices 280 thatare maintained by a particular entity at a particular location.Different custodians may maintain one or more of the different storagedevices. By way of example, referring to FIG. 15, the personal dataassociated with the Internet Usage History campaign 1510 may be storedin a repository located at the Toronto data center, and the repositorymay be controlled by the organization (e.g., Acme corporation) oranother entity, such as a vendor of the organization that has been hiredby the organization to analyze the customer's internet usage history.Alternatively, storage may be with a department within the organization(e.g., its marketing department). In example embodiments, clicking on(i.e., selecting) the column heading Destination 1525 may result in thecampaigns being sorted by destination.

On the inventory page 1500, the Access heading 1530 may show the numberof transfers that the personal data associated with a campaign hasundergone. In example embodiments, clicking on (i.e., selecting) thecolumn heading “Access” 1530 may result in the campaigns being sorted byAccess.

The column with the heading Audit 1535 shows the status of any privacyaudits associated with the campaign. Privacy audits may be pending, inwhich an audit has been initiated but yet to be completed. The auditcolumn may also show for the associated campaign how many days havepassed since a privacy audit was last conducted for that campaign.(e.g., 140 days, 360 days). If no audit for a campaign is currentlyrequired, an “OK” or some other type of indication of compliance (e.g.,a “thumbs up” indicia) may be displayed for that campaign's auditstatus. Campaigns may also be sorted based on their privacy audit statusby selecting or clicking on the Audit heading 1535.

In example inventory page 1500, an indicator under the heading Risk 1540may also display an indicator as to the Risk Level associated with thepersonal data for a particular campaign. As described earlier, a riskassessment may be made for each campaign based on one or more factorsthat may be obtained by the system. The indicator may, for example, be anumerical score (e.g., Risk Level of the campaign), or, as in theexample shown in FIG. 15, it may be arrows that indicate the OverallRisk Assessment for the campaign. The arrows may be of different shades,or different colors (e.g., red arrows indicating “high risk” campaigns,yellow arrows indicating “medium risk” campaigns, and green arrowsindicating “low risk” campaigns). The direction of the arrows—forexample, pointing upward or downward, may also provide a quickindication of Overall Risk Assessment for users viewing the inventorypage 1500. Each campaign may be sorted based on the Risk Levelassociated with the campaign.

The example inventory page 1500 may comprise a filter tool, indicated byFilters 1545, to display only the campaigns having certain informationassociated with them. For example, as shown in FIG. 15, under CollectionPurpose 1550, checking the boxes “Commercial Relations,” “ProvideProducts/Services”, “Understand Needs,” “Develop Business & Ops,” and“Legal Requirement” will result the display under the Data Flow Summary1505 of only the campaigns that meet those selected collection purposerequirements.

From example inventory page 1500, a user may also add a campaign byselecting (i.e., clicking on) Add Data Flow 1555. Once this selectionhas been made, the system initiates a routine to guide the user in aphase-by-phase manner through the process of creating a new campaign(further details herein). An example of the multi-phase GUIs in whichcampaign data associated with the added privacy campaign may be inputand associated with the privacy campaign record is described in FIG.8-13 above.

From the example inventory page 1500, a user may view the informationassociated with each campaign in more depth, or edit the informationassociated with each campaign. To do this, the user may, for example,click on or select the name of the campaign (i.e., click on InternetUsage History 1510). As another example, the user may select a buttondisplayed on screen indicating that the campaign data is editable (e.g.,edit button 1560).

I: FIG. 16: Campaign Information Page and Data Flow Diagram

FIG. 16 shows an example of information associated with each campaignbeing displayed in a campaign information page 1600. Campaigninformation page 1600 may be accessed by selecting (i.e., clicking on),for example, the edit button 1560. In this example, Personal DataCollected section 1605 displays the type of personal data collected fromthe customer for the campaign Internet Usage History. The type ofpersonal data, which may be stored as data elements associated with theInternet Usage History campaign digital record entry. The type ofinformation may include, for example, the customer's Subscriber ID,which may be assigned by the organization (e.g., a customeridentification number, customer account number). The type of informationmay also include data associated with a customer's premises equipment,such as an IP Address, MAC Address, URL History (i.e., websitesvisited), and Data Consumption (i.e., the number of megabytes orgigabytes that the user has download).

Still referring to FIG. 16, the “About this Data Flow” section 1610displays relevant information concerning the campaign, such as thepurpose of the campaign. In this example, a user may see that theInternet Usage History campaign is involved with the tracking ofinternet usage from customers in order to bill appropriately, manageagainst quotas, and run analytics. The user may also see that thebusiness group that is using the sensitive information associated withthis campaign is the Internet group. A user may further see that thenext privacy audit is scheduled for Jun. 10, 2016, and that the lastupdate of the campaign entry was Jan. 2, 2015. The user may also selectthe “view history” hyperlink to display the history of the campaign.

FIG. 16 also depicts an example of a Data Flow Diagram 1615 generated bythe system, based on information provided for the campaign. The DataFlow Diagram 1615 may provide the user with a large amount ofinformation regarding a particular campaign in a single compact visual.In this example, for the campaign Internet Usage History, the user maysee that the source of the personal data is the organization'scustomers. In example embodiments, as illustrated, hovering the cursor(e.g., using a touchpad, or a mouse) over the term “Customers” may causethe system to display the type of sensitive information obtained fromthe respective consumers, which may correspond with the informationdisplayed in the “Personal Data Collected” section 1605.

In various embodiments, the Data Flow Diagram 1615 also displays thedestination of the data collected from the User (in this example, anInternet Usage Database), along with associated parameters related tobackup and deletion. The Data Flow Diagram 1615 may also display to theuser which department(s) and what system(s) have access to the personaldata associated with the campaign. In this example, the Customer SupportDepartment has access to the data, and the Billing System may retrievedata from the Internet Usage Database to carry out that system'soperations. In the Data Flow Diagram 1615, one or more securityindicators may also be displayed. The may include, for example, an “eye”icon to indicate that the data is confidential, a “lock” icon toindicate that the data, and/or a particular flow of data, is encrypted,or an “unlocked lock” icon to indicate that the data, and/or aparticular flow of data, is not encrypted. In the example shown in FIG.16, the dotted arrow lines generally depict respective flows of data andthe locked or unlocked lock symbols indicate whether those data flowsare encrypted or unencrypted.

Campaign information page 1600 may also facilitate communications amongthe various personnel administrating the campaign and the personal dataassociated with it. Collaborators may be added through the Collaboratorsbutton 1625. The system may draw information from, for example, anactive directory system, to access the contact information ofcollaborators.

If comment 1630 is selected, a real-time communication session (e.g., aninstant messaging session) among all (or some) of the collaborators maybe instantiated and overlaid on top of the page 1600. This may behelpful, for example, in facilitating population of a particular page ofdata by multiple users. In example embodiments, the Collaborators 1625and Comments 1630 button may be included on any graphical user interfacedescribed herein, including dialog boxes in which information is enteredor selected. Likewise, any instant messaging session may be overlaid ontop of a webpage or dialog box. The system may also use the contactinformation to send one or more users associated with the campaignperiodic updates, or reminders. For example, if the deadline to finishentering the campaign data associated with a campaign is upcoming inthree days, the business representative of that assigned campaign may besent a message reminding him or her that the deadline is in three days.

Like inventory page 1500, campaign information page 1600 also allows forcampaigns to be sorted based on risk (e.g., Sort by Risk 1635). Thus,for example, a user is able to look at the information for campaignswith the highest risk assessment.

J: FIG. 17: Edit Campaign Dialog

FIG. 17 depicts an example of a dialog box—the edit campaign dialog1000. The edit campaign dialog 1000 may have editable fields associatedwith a campaign. In this example, the information associated with theInternet Usage History campaign 310 may be edited via this dialog. Thisincludes the ability for the user to change the name of the campaign,the campaign's description, the business group, the current owner of thecampaign, and the particular personal data that is associated with thecampaign (e.g., IP address, billing address, credit score, etc.). Inexample embodiments, the edit campaign dialog 1000 may also allow forthe addition of more factors, checkboxes, users, etc.

The system 100 also includes a Historical Record Keeping Module, whereinevery answer, change to answer, as well as assignment/re-assignment ofowners and collaborators is logged for historical record keeping.

Integrated/Automated Solution for Privacy Risk Assessments

The system may execute multiple integrated steps in assessing the riskof various privacy campaigns. For example, in a particular embodiment,the system first conducts a threshold privacy assessment (e.g., aPrivacy Threshold Analysis, or other threshold analysis) by asking auser a relatively short set of questions (e.g., between 1 and 15questions) to quickly determine whether the risk associated with aparticular privacy campaign exceeds a pre-determined privacy riskthreshold value. This information may be used to determine that theprivacy campaign requires a full privacy impact assessment (which wouldbe the case if the risk associated with the privacy campaign is abovethe privacy risk threshold value), or alternatively that the privacycampaign is a relatively low-risk campaign that wouldn't require aprivacy impact assessment.

In conducting the threshold privacy assessment, the system may use anyof the above techniques (e.g., the techniques described above withrespect to the Risk Assessment Module 430) to assign an initialcollective privacy risk score to the user's answers to the brief set ofthreshold questions. The system then determines whether the initialcollective privacy risk score exceeds the privacy risk threshold value.

In various embodiments, the system may be configured for, in response tothe user's answers to one or more of the questions within the thresholdprivacy assessment indicating that the campaign exceeds a pre-determinedprivacy risk threshold, presenting the user with additional questionsregarding the privacy campaign (e.g., a full privacy impact assessment).In various embodiments, these additional questions may be more detailedthan the one or more questions in the threshold privacy assessmentand/or the number of questions in the set of additional questions may begreater than the number of questions within the threshold privacyassessment. After receiving the user's answers to these additionalquestions, the system may use the user's answers to the additionalquestions to assess the overall risk of the campaign, for example, asdescribed above.

As noted above, in particular embodiments, the system may be configuredfor, in response to the user's answers to one or more of the questionswithin the threshold privacy assessment indicating that the campaigndoes not exceed the privacy risk threshold, not presenting the user witha supplemental set of questions regarding the campaign (e.g., a privacyimpact assessment). In such a case, the system may simply save anindication to memory that the campaign is a relatively low riskcampaign.

Accordingly, in particular embodiments, the system may be adapted toautomatically initiate a full privacy impact assessment if the resultsof a shorter threshold privacy assessment satisfy certain criteria.Additionally, or alternatively, in particular embodiments, the systemmay be adapted to allow a privacy officer to manually initiate a fullprivacy impact assessment for a particular campaign regardless of thecampaign's initial collective privacy risk score.

In particular embodiments, built into the threshold privacy assessmentand the privacy impact assessment are data mapping questions and/orsub-questions of how the personal data obtained through the campaignwill be collected, used, stored, accessed, retained, and/or transferred,etc. In particular embodiments: (1) one or more of these questions areasked in the threshold privacy assessment; and (2) one or more of thequestions are asked in the full privacy impact assessment. In suchembodiments, the system may obtain the answers to each of thesequestions, as captured during the threshold privacy assessment and theprivacy impact assessment, and then use the respective answers togenerate an end-to-end data flow for the relevant privacy campaign.

The system may then link all of the data flows across all of theorganization's privacy campaigns together in order to show a completeevergreen version of the personal data inventory of the organization.Thus, the system may efficiently generate the personal data inventory ofan organization (e.g., through the use of reduced computer processingpower) by automatically gathering the data needed to prepare thepersonal data inventory while conducting threshold privacy assessmentsand privacy impact assessments for various privacy campaigns.

More Detailed Discussion

The “Integrated/Automated Solution for Privacy Risk Assessments” conceptdescribed generally above is described in greater detail below.

A. Threshold Privacy Assessment

In various embodiments, the system may present a threshold privacyassessment to a user in response to the user inputting, into the system,a request to initiate a privacy campaign. The threshold privacyassessment may include a first set of one or more questions for a firstplurality of question/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign. The thresholdprivacy assessment may present the user or a plurality of users (e.g.,software or other product developers) with a series of questions (whichmay be done, for example, using a suitable “wizard” program) regardingprivacy characteristics of the campaign—e.g., how the product willcollect, use, store, and/or manage personal data.

Determination of Initial Collective Risk Score

After receiving the respective answers to the questions of the firstplurality of question/answer pairings, the privacy assessment module maycalculate an initial collective privacy risk score for the particularprivacy campaign that identifies a level of risk for one or more of theprivacy characteristics indicated in the first plurality ofquestion/answer pairings. The system may do this, for example, by usingany of the above techniques to assign an initial collective privacy riskscore to the user's answers to the questions and then determiningwhether the collective privacy risk score exceeds a particular,pre-determined privacy risk threshold value.

In various embodiments, the system may calculate, or otherwisedetermine, the initial collective privacy risk score based on adetermined level of risk for each of the privacy characteristicsidentified in the first plurality of question/answer pairings. Inparticular embodiments, the system may determine the initial collectiveprivacy risk score, and any other risk score discussed in this section,generally as described above in regard to the Risk Assessment Module430. For example, the system may allow the answers to various questionsto be weighted according to importance for purposes of the riskcalculation as described above.

B. Automatic Initiation of Privacy Impact Assessment Upon Receiving Oneor More High-Risk Answers

In some embodiments, the system is adapted so that, if a particularresponse is provided to a question related to a particular privacycharacteristic, the automatically determines that the privacy campaignis not a low-risk campaign and initiates a full privacy impactassessment for the privacy campaign. For example, if a user answers aquestion, in the course of completing the threshold privacy assessment,that the system collects users' credit card information, then the systemmay automatically determine that the privacy campaign is not a low-riskcampaign and may initiate a full privacy impact assessment for theprivacy campaign.

The system may implement this concept, for example, by assigning avalue, to a particular answer for a particular question, that exceedsthe privacy risk threshold value. Accordingly, since, in variousembodiments, answers to threshold privacy assessment questions are notassigned negative values, in such situations, the initial collectiveprivacy risk score will always exceed the privacy risk threshold valueif the system receives the particular answer to the particular questionwithin the threshold privacy assessment.

C. Comparison of Initial Privacy Risk Score with Privacy Risk ThresholdValue

After the system determines the initial collective privacy risk score,the system compares the initial privacy collective privacy risk score toa pre-determined privacy risk threshold value, which corresponds to amaximum level of risk that the system will allow without requiring afull privacy impact assessment to be conducted for a particular privacycampaign. The privacy risk threshold value may, for example: (1) be setby a privacy officer assigned to the initiated privacy campaign, or anyother suitable individual; (2) be a default value (e.g., which may beadjustable by a suitable individual, such as a privacy officer), or (3)be automatically determined by the system in any suitable way.

In some embodiments, the system may automatically determine the privacyrisk threshold value based, at least in part, on a campaign typeassociated with the initiated privacy campaign. For example, the systemmay be adapted to determine and use a relatively higher privacy riskthreshold value for business activities that involve the collection ofpersonally identifiable information than business activities that onlycollect non-personally identifiable information.

D. Actions Taken if Initial Privacy Risk Score Doesn't Exceed PrivacyRisk Threshold Value

As noted above, in particular embodiments, the system may be configuredfor, in response to the user's answers to one or more of the questionswithin the threshold privacy assessment indicating that the campaigndoes not exceed the privacy risk threshold, not initiating a privacyimpact assessment. In such a case, the system may simply save anindication to memory that the campaign is a relatively low riskcampaign.

E. Actions Taken if Initial Privacy Risk Score Exceeds Privacy RiskThreshold Value

In various embodiments, the system, in response to determining that theinitial collective privacy risk score exceeds the privacy risk thresholdvalue for the particular campaign, automatically initiates a privacyrisk assessment by, for example, communicating (e.g., displaying on acomputer display screen) a second set of questions to the user. Thesecond set of questions may seek additional, and/or more detailed,information regarding the privacy campaign. In some implementations, thesecond set of one or more questions includes a greater number ofquestions than the first set of one or more questions. For example, if,in the first set of questions, the user indicated that personal dataobtained during the privacy campaign will be stored, in system memory,for five years, then in the second set of questions, the system may askwhy the personal data will be stored for so long and who will haveaccess to the data after the privacy campaign has been completed.

In some implementations, the system, when executing the privacyassessment module, may communicate a notification to a privacy officerassociated with the campaign to indicate if the initial collectiveprivacy risk score for a particular privacy campaign exceeds the privacyrisk threshold value. Additionally, in some implementations, the systemmay determine whether the initial collective privacy risk score exceedsthe privacy risk threshold value, and then (e.g., in response) provideone or more selection options to one or more privacy officers associatedwith the campaign to address this fact. For example, the system mayprovide the one or more privacy officers with a first selection optionthat, if selected, initiates a privacy impact assessment for the privacycampaign (in various embodiments, this may be done by the privacyofficer even if the initial collective privacy risk score for thecampaign is below the privacy risk threshold value), and the system mayprovide the privacy officer with a second selection option that, ifselected, manually overrides the system's initial automaticdetermination that the particular privacy campaign is not a low-riskcampaign. In various embodiments, if the privacy officer selects thissecond selection option, the system saves, to memory, an indication thatthe privacy campaign is a low-risk campaign and/or doesn't implement aprivacy impact assessment for the privacy campaign.

F. Determination of Updated Privacy Risk Score

In various embodiments, if the system executes a full privacy impactassessment for the privacy campaign, the system receives the respectiveanswers for the second plurality of question/answer pairings, and thenautomatically determines an updated privacy risk score for theparticular privacy campaign that indicates a level of risk for one ormore of the privacy characteristics indicated in the second plurality ofquestion/answer pairings.

In particular embodiments, the system is configured to use the updatedprivacy risk score to assess the risk level of the privacy campaign asdiscussed elsewhere herein. In particular embodiments, the system mayuse the privacy risk threshold value in determining whether tocategorize the privacy campaign as a relatively low risk campaign. Forexample, in a particular embodiment, the system will store an indicationin memory that the privacy campaign is a relatively low risk campaign inresponse to the updated risk score being less than, or equal to, therisk threshold score.

G. Execution of Advanced Privacy Impact Assessment

In some implementations, when the updated privacy risk score exceeds thethreshold privacy risk value or other predetermined value, the system isconfigured to provide an advanced privacy impact assessment to the userthat includes a third set of questions for a third plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign. The third set of oneor more questions may include additional supplemental questions that areprovided to further inquire about privacy characteristics associatedwith the privacy campaign. The system may then provide a further updatedrisk score for the privacy campaign based, at least in part, on theanswers to these questions.

Additional Aspects of System

1. Standardized and Customized Assessment of Vendors' Compliance withPrivacy and/or Security Policies

In particular embodiments, the system may be adapted to: (1) facilitatethe assessment of one or more vendors' compliance with one or moreprivacy and/or security policies; and (2) allow organizations (e.g.,companies or other organizations) who do business with the vendors tocreate, view and/or apply customized criteria to informationperiodically collected by the system to evaluate each vendor'scompliance with one or more of the company's specific privacy and/orsecurity policies. In various embodiments, the system may also flag anyassessments, projects, campaigns, and/or data flows that theorganization has documented and maintained within the system if thosedata flows are associated with a vendor that has its rating changed sothat the rating meets certain criteria (e.g., if the vendor's ratingfalls below a predetermined threshold).

In particular embodiments:

-   -   The system may include an online portal and community that        includes a listing of all supported vendors.    -   An appropriate party (e.g., the participating vendor or a member        of the on-line community) may use the system to submit an        assessment template that is specific to a particular vendor.        -   If the template is submitted by the vendor itself, the            template may be tagged in any appropriate way as “official”        -   An instance for each organization using the system (i.e.,            customer) is integrated with this online community/portal so            that the various assessment templates can be directly fed            into that organization's instance of the system if the            organization wishes to use it.    -   Vendors may subscribe to a predetermined standardized assessment        format.        -   Assessment results may also be stored in the central            community/portal.        -   A third-party privacy and/or security policy compliance            assessor, on a schedule, may (e.g., periodically) complete            the assessment of the vendor.        -   Each organization using the system can subscribe to the            results (e.g., once they are available).        -   Companies can have one or more customized rules set up            within the system for interpreting the results of            assessments in their own unique way. For example:            -   Each customer can weight each question within an                assessment as desired and set up addition/multiplication                logic to determine an aggregated risk score that takes                into account the customized weightings given to each                question within the assessment.            -   Based on new assessment results—the system may notify                each customer if the vendor's rating falls, improves, or                passes a certain threshold.            -   The system can flag any assessments, projects,                campaigns, and/or data flows that the customer has                documented and maintained within the system if those                data flows are associated with a vendor that has its                rating changed.                2. Privacy Policy Compliance System that Facilitates                Communications with Regulators (Including Translation                Aspect)

In particular embodiments, the system is adapted to interface with thecomputer systems of regulators (e.g., government regulatory agencies)that are responsible for approving privacy campaigns. This may, forexample, allow the regulators to review privacy campaign informationdirectly within particular instances of the system and, in someembodiments, approve the privacy campaigns electronically.

In various embodiments, the system may implement this concept by:

-   -   Exporting relevant data regarding the privacy campaign, from an        organization's instance of the system (e.g., customized version        of the system) in standardized format (e.g., PDF or Word) and        sending the extracted data to an appropriate regulator for        review (e.g., in electronic or paper format).        -   Either regular provides the format that the system codes to,            or the organization associated with the system provides a            format that the regulators are comfortable with.    -   Send secure link to regulator that gives them access to comment        and leave feedback        -   Gives the regulator direct access to the organization's            instance of the system with a limited and restricted view of            just the projects and associated audit and commenting logs            the organization needs reviewed.        -   Regulator actions are logged historically and the regulator            can leave guidance, comments, and questions, etc.    -   Have portal for regulator that securely links to the systems of        their constituents.

Details:

-   -   When submitted—the PIAs are submitted with requested        priority—standard or expedited.    -   DPA specifies how many expedited requests individuals are        allowed to receive.    -   Either the customer or DPA can flag a PIA or associated        comments/guidance on the PIA with “needs translation” and that        can trigger an automated or manual language translation.    -   Regulator could be a DPA “data protection authority” in any EU        country, or other country with similar concept like FTC in US,        or OPC in Canada.        3. Systems/Methods for Measuring the Privacy Maturity of a        Business Group within an Organization.

In particular embodiments, the system is adapted for automaticallymeasuring the privacy of a business group, or other group, within aparticular organization that is using the system. This may provide anautomated way of measuring the privacy maturity, and one or more trendsof change in privacy maturity of the organization, or a selectedsub-group of the organization.

In various embodiments, the organization using the system can customizeone or more algorithms used by the system to measure the privacymaturity of a business group (e.g., by specifying one or more variablesand/or relative weights for each variable in calculating a privacymaturity score for the group). The following are examples of variablesthat may be used in this process:

-   -   Issues/Risks found in submitted assessments that are unmitigated        or uncaught prior to the assessment being submitted to the        privacy office        -   % of privacy assessments with high issues/total assessments        -   % with medium        -   % with low    -   Size and type of personal data used by the group        -   Total assessments done        -   Number of projects/campaigns with personal data        -   Amount of personal data        -   Volume of data transfers to internal and external parties    -   Training of the people in the group        -   Number or % of individuals who have watched training,            readings, or videos        -   Number or % of individuals who have completed quizzes or            games for privacy training        -   Number or % of individuals who have attended privacy events            either internally or externally        -   Number or % of individuals who are members of IAPP        -   Number or % of individuals who have been specifically            trained in privacy either internally or externally, formally            (IAPP certification) or informally        -   Usage of an online version of the system, or mobile training            or communication portal that customer has implemented    -   Other factors        4. Automated Assessment of Compliance (Scan App or Website to        Determine Behavior/Compliance with Privacy Policies)

In various embodiments, instead of determining whether an organizationcomplies with the defined parameters of a privacy campaign by, forexample, conducting an audit as described above (e.g., by asking usersto answer questions regarding the privacy campaign, such as “What iscollected” “what cookies are on your website”, etc.), the system may beconfigured to automatically determine whether the organization iscomplying with one or more aspects of the privacy policy.

For example, during the audit process, the system may obtain a copy of asoftware application (e.g., an “app”) that is collecting and/or usingsensitive user information, and then automatically analyze the app todetermine whether the operation of the app is complying with the termsof the privacy campaign that govern use of the app.

Similarly, the system may automatically analyze a website that iscollecting and/or using sensitive user information to determine whetherthe operation of the web site is complying with the terms of the privacycampaign that govern use of the web site.

In regard to various embodiments of the automatic application-analyzingembodiment referenced above:

-   -   The typical initial questions asked during an audit may be        replaced by a request to “Upload your app here”.        -   After the app is uploaded to the system, the system detects            what privacy permissions and data the app is collecting from            users.        -   This is done by having the system use static or behavioral            analysis of the application, or by having the system            integrate with a third-party system or software (e.g.,            Veracode), which executes the analysis.        -   During the analysis of the app, the system may detect, for            example, whether the app is using location services to            detect the location of the user's mobile device.        -   In response to determining that the app is collecting one or            more specified types of sensitive information (e.g., the            location of the user's mobile device), the system may            automatically request follow up information from the user by            posing one or more questions to the user, such as:            -   For what business reason is the data being collected?            -   How is the user's consent given to obtain the data?            -   Would users be surprised that the data is being                collected?            -   Is the data encrypted at rest and/or in motion?            -   What would happen if the system did not collect this                data? What business impact would it have?            -   In various embodiments, the system is adapted to allow                each organization to define these follow-up questions,                but the system asks the questions (e.g., the same                questions, or a customized list of questions) for each                privacy issue that is found in the app.        -   In various embodiments, after a particular app is scanned a            first time, when the app is scanned, the system may only            detect and analyze any changes that have been made to the            app since the previous scan of the app.        -   In various embodiments, the system is adapted to            (optionally) automatically monitor (e.g., continuously            monitor) one or more online software application            marketplaces (such as Microsoft, Google, or Apple's App            Store) to determine whether the application has changed. If            so, the system may, for example: (1) automatically scan the            application as discussed above; and (2) automatically notify            one or more designated individuals (e.g., privacy office            representatives) that an app was detected that the business            failed to perform a privacy assessment on prior to launching            the application.

In regard to various embodiments of the automatic application-analyzingembodiment referenced above:

-   -   The system prompts the user to enter the URL of the website to        be analyzed, and, optionally, the URL to the privacy policy that        applies to the web site.    -   The system then scans the website for cookies, and/or other        tracking mechanisms, such as fingerprinting technologies and/or        3rd party SDKs.        -   The system may then optionally ask the user to complete a            series of one or more follow-up questions for each of these            items found during the scan of the website.        -   This may help the applicable privacy office craft a privacy            policy to be put on the website to disclose the use of the            tracking technologies and SDK's used on the website.    -   The system may then start a continuous monitoring of the website        site to detect whether any new cookies, SDKs, or tracking        technologies are used. In various embodiments, the system is        configured to, for example, generate an alert to an appropriate        individual (e.g., a designated privacy officer) to inform them        of the change to the website. The privacy officer may use this        information, for example, to determine whether to modify the        privacy policy for the website or to coordinate discontinuing        use of the new tracking technologies and/or SDK's.    -   In various embodiments, the system may also auto-detect whether        any changes have been made to the policy or the location of the        privacy policy link on the page and, in response to        auto-detecting such changes, trigger an audit of the project.    -   It should be understood that the above methods of automatically        assessing behavior and/or compliance with one or more privacy        policies may be done in any suitable way (e.g., ways other than        website scanning and app scanning). For example, the system may        alternatively, or in addition, automatically detect, scan and/or        monitor any appropriate technical system(s) (e.g., computer        system and/or system component or software), cloud services,        apps, websites and/or data structures, etc.        5. System Integration with DLP Tools.

DLP tools are traditionally used by information security professionals.Various DLP tools discover where confidential, sensitive, and/orpersonal information is stored and use various techniques toautomatically discover sensitive data within a particular computersystem—for example, in emails, on a particular network, in databases,etc. DLP tools can detect the data, what type of data, the amount ofdata, and whether the data is encrypted. This may be valuable forsecurity professionals, but these tools are typically not useful forprivacy professionals because the tools typically cannot detect certainprivacy attributes that are required to be known to determine whether anorganization is in compliance with particular privacy policies.

For example, traditional DLP tools cannot typically answer the followingquestions:

-   -   Who was the data collected from (data subject)?    -   Where are those subjects located?    -   Are they minors?    -   How was consent to use the data received?    -   What is the use of the data?    -   Is the use consistent with the use specified at the time of        consent?    -   What country is the data stored in and/or transferred to?    -   Etc.    -   In various embodiments, the system is adapted to integrate with        appropriate DLP and/or data discovery tools (e.g., INFORMATICA)        and, in response to data being discovered by those tools, to        show each area of data that is discovered as a line-item in a        system screen via integration.    -   The system may do this, for example, in a manner that is similar        to pending transactions in a checking account that have not yet        been reconciled.    -   A designated privacy officer may then select one of those—and        either match it up (e.g., reconcile it) with an existing data        flow or campaign in the system OR trigger a new assessment to be        done on that data to capture the privacy attributes and data        flow.        6. System for Generating an Organization's Data Map by Campaign,        by System, or by Individual Data Attributes.

In particular embodiments, the system may be adapted to allow users tospecify various criteria, and then to display, to the user, any datamaps that satisfy the specified criteria. For example, the system may beadapted to display, in response to an appropriate request: (1) all of aparticular customer's data flows that are stored within the system; (2)all of the customer's data flows that are associated with a particularcampaign; and/or (3) all of the customer's data flows that involve aparticular address.

Similarly, the system may be adapted to allow privacy officers todocument and input the data flows into the system in any of a variety ofdifferent ways, including:

-   -   Document by process        -   The user initiates an assessment for a certain business            project and captures the associated data flows (including            the data elements related to the data flows and the systems            they are stored in).    -   Document by element        -   The user initiates an audit of a data element—such as            SSN—and tries to identify all data structures associated            with the organization that include the SSN. The system may            then document this information (e.g., all of the            organization's systems and business processes that involve            the business processes.)    -   Document by system        -   The user initiates an audit of a database, and the system            records, in memory, the results of the audit.            7. Privacy Policy Compliance System that Allows Users to            Attach Emails to Individual Campaigns.

Privacy officers frequently receive emails (or other electronicmessages) that are associated with an existing privacy assessment orcampaign, or a potential future privacy assessment. For record keepingand auditing purposes, the privacy officer may wish to maintain thoseemails in a central storage location, and not in email. In variousembodiments, the system is adapted to allow users to automaticallyattach the email to an existing privacy assessment, data flow, and/orprivacy campaign. Alternatively or additionally, the system may allow auser to automatically store emails within a data store associated withthe system, and to store the emails as “unassigned”, so that they maylater be assigned to an existing privacy assessment, data flow, and/orprivacy campaign.

-   -   In various embodiments, the system is adapted to allow a user to        store an email using:        -   a browser plugin-extension that captures webmail;        -   a Plug-in directly with office 365 or google webmail (or            other suitable email application);        -   a Plug-in with email clients on computers such as Outlook;        -   via an integrated email alias that the email is forwarded            to; or        -   any other suitable configuration            8. Various Aspects of Related Mobile Applications

In particular embodiments, the system may use a mobile app (e.g., thatruns on a particular mobile device associated by a user) to collect datafrom a user. The mobile app may be used, for example, to collect answersto screening questions. The app may also be adapted to allow users toeasily input data documenting and/or reporting a privacy incident. Forexample, the app may be adapted to assist a user in using their mobiledevice to capture an image of a privacy incident (e.g., a screen shotdocumenting that data has been stored in an improper location, or that aprintout of sensitive information has been left in a public workspacewithin an organization.)

The mobile app may also be adapted to provide incremental training toindividuals. For example, the system may be adapted to provideincremental training to a user (e.g., in the form of the presentation ofshort lessons on privacy). Training sessions may be followed by shortquizzes that are used to allow the user to assess their understanding ofthe information and to confirm that they have completed the training.

9. Automatic Generation of Personal Data Inventory for Organization

In particular embodiments, the system is adapted to generate and displayan inventory of the personal data that an organization collects andstores within its systems (or other systems). As discussed above, invarious embodiments, the system is adapted to conduct privacy impactassessments for new and existing privacy campaigns. During a privacyimpact assessment for a particular privacy campaign, the system may askone or more users a series of privacy impact assessment questionsregarding the particular privacy campaign and then store the answers tothese questions in the system's memory, or in memory of another system,such a third-party computer server.

Such privacy impact assessment questions may include questionsregarding: (1) what type of data is to be collected as part of thecampaign; (2) who the data is to be collected from; (3) where the datais to be stored; (4) who will have access to the data; (5) how long thedata will be kept before being deleted from the system's memory orarchived; and/or (6) any other relevant information regarding thecampaign.

The system may store the above information, for example, in any suitabledata structure, such as a database. In particular embodiments, thesystem may be configured to selectively (e.g., upon request by anauthorized user) generate and display a personal data inventory for theorganization that includes, for example, all of the organization'scurrent active campaigns, all of the organization's current and pastcampaigns, or any other listing of privacy campaigns that, for example,satisfy criteria specified by a user. The system may be adapted todisplay and/or export the data inventory in any suitable format (e.g.,in a table, a spreadsheet, or any other suitable format).

Automated Approach to Demonstrating Privacy by Design

Privacy by design is a documented approach to managing privacy risks.One of the primary concepts is evaluating privacy impacts, and makingappropriate privacy-protecting changes during the design phase of aproject, before the project go-live. Organizations have embraced theconcept, but have struggled with how to operationalize and demonstratethat they are doing this.

In various embodiments, the system is adapted to automate this with thefollowing capabilities: (1) initial assessment; (2) gapanalysis/recommendations; and/or (3) final/updated assessment. Thesecapabilities are discussed in greater detail below.

Initial Assessment

In various embodiments, when a business team within a particularorganization is planning to begin a privacy campaign, the systempresents the business team with a set of assessment questions that aredesigned to help one or more members of the organization's privacy teamto understand what the business team's plans are, and to understandwhether the privacy campaign may have privacy impact on theorganization. The questions may also include a request for the businessteam to provide the “go-live” date for the privacy campaign. In responseto receiving the answers to these questions, the system stores theanswers to the system's memory and makes the answers available to theorganization's privacy team. The system may also add the “go-live” dateto one or more electronic calendars (e.g., the system's electronicdocket).

Gap Analysis/Recommendations

After the system receives the answers to the questions, one or moremembers of the privacy team may review the answers to the questions. Theprivacy team may then enter, into the system, guidance and/orrecommendations regarding the privacy campaign. In particularembodiments, the system automatically reminds one or more members of thebusiness team to implement the privacy team's recommendations before thego-live date. The system may also implement one or more audits (e.g., asdescribed above) to make sure that the business team incorporates theprivacy team's recommendations before the “go-live” date.

Final/Updated Assessment

Once the mitigation steps and recommendations are complete, the systemmay (e.g., automatically) conduct an updated review to assess theupdated privacy impact and privacy risks.

Reporting and Historical Logging Capabilities

In particular embodiments, the system includes unique reporting andhistorical logging capabilities to automate Privacy-by-Design reporting.In various embodiments, the system is adapted to: (1) measure/analyzethe initial assessment answers from the business team; (2) measurerecommendations for the privacy campaign; (3) measure any changes thatwere implemented prior to the go-live date; (4) automaticallydifferentiate between: (a) substantive privacy protecting changes, suchas the addition of encryption, anonymization, or minimizations; and (b)non-substantive changes, such as spelling correction.

The system may also be adapted to generate a privacy-by-design reportshowing that: (1) projects are evaluated prior to go-live; and (2)substantive recommendations are made and implemented prior to go-live.This may be useful in documenting that privacy-by-design is beingeffectively implemented for a particular privacy campaign.

System for Preventing Individuals from Trying to Game the System

As discussed above, in particular embodiments, the system is adapted todisplay a series of threshold questions for particular privacy campaignsand to use conditional logic to assess whether to present additional,follow-up questions to the user. There may be situations in which a usermay answer, or attempt to answer, one or more of the threshold questionsincorrectly (e.g., dishonestly) in an attempt to avoid needing to answeradditional questions. This type of behavior can present seriouspotential problems for the organization because the behavior may resultin privacy risks associated with a particular privacy campaign beinghidden due to the incorrect answer or answers.

To address this issue, in various embodiments, the system: (1) maintainsa historical record of every button press (e.g., un-submitted systeminput) that an individual makes when a question is presented to them;and (2) tracks, and saves to memory, each incidence of the individualchanging their answer to a question (e.g., (a) before formallysubmitting the answer by pressing an “enter” key, or other “submit” keyon a user interface, such as a keyboard or graphical user interface on atouch-sensitive display screen; or (b) after initially submitting theanswer).

The system may also be adapted to automatically determine whether aparticular question (e.g., threshold question) is a “critical” questionthat, if answered in a certain way, would cause the conditional logictrigger to present the user with one or more follow-up questions. Forexample, the system may, in response to receiving the user's full set ofanswers to the threshold questions, automatically identify anyindividual question within the series of threshold questions that, ifanswered in a particular way (e.g., differently than the user answeredthe question) would have caused the system to display one or more followup questions. The system may then flag those identified questions, inthe system's memory, as “critical” questions.

Alternatively, the system may be adapted to allow a user (e.g., aprivacy officer of an organization) who is drafting a particularthreshold question that, when answered in a particular way, willautomatically trigger the system to display one or more follow upquestions to the user, to indicate that is a “critical” thresholdquestion. The system may then save this “critical” designation of thequestion to the system's computer memory.

In various embodiments, the system is configured, for any questions thatare deemed “critical” (e.g., either by the system, or manually, asdiscussed above), to determine whether the user exhibited any abnormalbehavior when answering the question. For example, the system may checkto see whether the user changed their answer once, or multiple times,before submitting their answer to the question (e.g., by tracking theuser's keystrokes while they are answering the threshold question, asdescribed above). As another example, the system may determine whetherit took the user longer than a pre-determined threshold amount of time(e.g., 5 minutes, 3 minutes, etc.) to answer the critical thresholdquestion.

In particular embodiments, the system may be adapted, in response todetermining that the user exhibited abnormal behavior when answering thecritical threshold question, to automatically flag the thresholdquestion and the user's answer to that question for later follow up by adesignated individual or team (e.g., a member of the organization'sprivacy team). In particular embodiments, the system may also, oralternatively, be adapted to automatically generate and transmit amessage to one or more individuals (e.g., the organization's chiefprivacy officer) indicating that the threshold question may have beenanswered incorrectly and that follow-up regarding the question may beadvisable. After receiving the message, the individual may, inparticular embodiments, follow up with the individual who answered thequestion, or conduct other additional research, to determine whether thequestion was answered accurately.

CONCLUSION

Although embodiments above are described in reference to various systemsand methods for creating and managing data flows related to individualprivacy campaigns, it should be understood that various aspects of thesystem described above may be applicable to other privacy-relatedsystems, or to other types of systems, in general. For example, thefunctionality described above for obtaining the answers to variousquestions (e.g., assigning individual questions or sections of questionsto multiple different users, facilitating collaboration between theusers as they complete the questions, automatically reminding users tocomplete their assigned questions, and other aspects of the systems andmethods described above) may be used within the context of privacyimpact assessments (e.g., in having users answer certain questions todetermine whether a certain project complies with an organization'sprivacy policies).

While this specification contains many specific embodiment details,these should not be construed as limitations on the scope of anyinvention or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularinventions. Certain features that are described in this specification inthe context of separate embodiments may also be implemented incombination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment may also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination may in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems maygenerally be integrated together in a single software product orpackaged into multiple software products.

Many modifications and other embodiments of the invention will come tomind to one skilled in the art to which this invention pertains havingthe benefit of the teachings presented in the foregoing descriptions andthe associated drawings. While examples discussed above cover the use ofvarious embodiments in the context of operationalizing privacycompliance and assessing risk of privacy campaigns, various embodimentsmay be used in any other suitable context. Therefore, it is to beunderstood that the invention is not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for the purposes of limitation.

What is claimed is:
 1. A computer-implemented data processing method forefficiently conducting privacy risk assessments for a plurality ofprivacy campaigns, the method comprising, for each of the plurality ofprivacy campaigns: presenting, by one or more processors, a thresholdprivacy assessment to a user that includes a first set of one or morequestions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of a particular privacycampaign; receiving, by one or more processors, respective answers forthe first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign;determining, by one or more processors, a threshold privacy risk scorefor the particular privacy campaign that identifies a level of risk forone or more of the privacy characteristics indicated in thequestion/answer pairings, wherein determining the threshold privacy riskscore for the particular privacy campaign comprises: electronicallydetermining a risk level based at least in part on the one or moreprivacy characteristics, wherein the one or more privacycharacterisitics include an indication of a nature of personal datacollected by the particular privacy campaign; comparing, by one or moreprocessors, the threshold privacy risk score to a threshold privacy riskvalue, the threshold privacy risk value indicating a pre-determinedlevel of risk regarding the one or more privacy characteristics of theparticular privacy campaign; determining, by one or more processors,whether the threshold privacy risk score exceeds the threshold privacyrisk value; in response to determining that the threshold privacy riskscore exceeds the threshold privacy risk value: providing, by one ormore processors, a privacy impact assessment to the user that includes asecond set of questions for a second plurality of question/answerpairings that identify one or more privacy characteristics of theparticular privacy campaign, the second set of one or more questionsincluding one or more questions that are different from questions withinthe first set of one or more questions; and determining by one or moreprocessors, a second risk score based at least in part on the secondplurality of question answer parings by: determining a weighting factorfor each of the second plurality of question/answer parings, the secondplurality of question/answer parings including: an indication of aphysical storage location of the personal data collected as part of theparticular privacy campaign; and an indication of a length of time thatthe personal data collected as part of the particular privacy campaignwill be stored in the physical storage location; electronicallydetermining a relative risk rating for each of the second plurality ofquestion/answer pairings; electronically calculating the second riskscore based upon, for each of the second plurality of question/answerpairings, the relative risk rating and the weighting factor; andelectrically associating the second risk score with the particularprivacy campaign; and in response to determining that the privacy riskscore does not exceed the threshold privacy risk value, storing, by oneor more processors, an indication that the particular privacy campaignis a low privacy risk campaign.
 2. The computer-implemented dataprocessing method of claim 1, wherein the threshold privacy risk scoreis determined by associating a weight for each question in the first setof questions.
 3. The computer-implemented data processing method ofclaim 2, wherein associating a weight for each question in the first setof questions further comprises: determining that a first question in thefirst set of questions identifies a greater privacy impact than a secondquestion in the first set of questions; and assigning a weight to thefirst question in the first set of questions that is greater than aweight to be assigned to the second question in the first set ofquestions.
 4. The computer-implemented data processing method of claim1, wherein determining the threshold privacy risk score for theparticular campaign further comprises: determining that a question in aparticular question/answer pairing for the first plurality ofquestion/answer pairings includes an answer, for the particularquestion/answer pairing, that provides a particular response; andautomatically determining that the threshold privacy risk score for theparticular privacy campaign exceeds the threshold privacy risk value. 5.The computer-implemented data processing method of claim 1, wherein inresponse to determining that the threshold privacy risk score exceedsthe threshold privacy risk value, the method further comprises:providing, by the one or more processors, a notification to one or moreprivacy officers associated with the privacy campaign to indicate thatthe threshold privacy risk score exceeds the threshold privacy riskvalue.
 6. The computer-implemented data processing method of claim 1,further comprising: in response to determining that the thresholdprivacy risk score exceeds the threshold privacy risk value, providing,by the one or more processors, the privacy impact assessment to the userthat includes a second set of questions for a second plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign; receiving, by theone or more processors, respective answers for the second plurality ofquestion/answer pairings regarding the one or more privacycharacteristics of the particular privacy campaign; determining, by theone or more processors, an updated privacy risk score for the particularprivacy campaign that identifies a level of risk for one or more of theprivacy characteristics indicated in the second plurality ofquestion/answer pairings; comparing, by the one or more processors, theupdated privacy risk score to the threshold privacy risk value, thethreshold privacy risk value indicating a pre-determined level of riskregarding the one or more privacy characteristics of the particularprivacy campaign; determining, by the one or more processors, whetherthe updated privacy risk score exceeds the threshold privacy risk value;in response to determining that the privacy risk score exceeds thethreshold privacy risk value, providing, by the one or more processors,a notification to one or more privacy officers associated with theprivacy campaign that the particular privacy campaign is a high privacyrisk campaign; and in response to determining that the privacy riskscore does not exceed the threshold privacy risk value, storing, by theone or more processors, the indication that the particular privacycampaign is a low privacy risk campaign.
 7. The computer-implementeddata processing method of claim 1, wherein the threshold privacy riskvalue is configured to be set by one or more privacy officers associatedwith the privacy campaign.
 8. The computer-implemented data processingmethod of claim 7, wherein the threshold privacy risk value isconfigured to be adjusted based on a type of campaign for the particularprivacy campaign.
 9. A computer-implemented data processing method forefficiently conducting privacy risk assessments for a plurality ofprivacy campaigns, the method comprising, for each of the plurality ofprivacy campaigns: presenting, by one or more processors, a thresholdprivacy assessment to a user that includes a first set of one or morequestions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of the particular privacycampaign; receiving, by one or more processors, respective answers forthe first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign;determining, by one or more processors, a privacy risk score for theparticular privacy campaign that identifies a level of risk for one ormore of the privacy characteristics indicated in the question/answerpairings; comparing, by one or more processors, the privacy risk scoreto a threshold privacy risk value, the threshold privacy risk valueindicating a pre-determined level of risk regarding the one or moreprivacy characteristics of the particular privacy campaign; determining,by one or more processors, whether the privacy risk score exceeds thethreshold privacy risk value; providing, by one or more processors andto one or more privacy officers, (1) a first selection option toinitiate a privacy impact assessment to be provided to the user thatincludes a second set of questions for a second plurality ofquestion/answer pairings that identify one or more privacycharacteristics of the particular privacy campaign, the second set ofone or more questions includes one or more questions that aresupplemental to the first set of one or more questions and (2) a secondselection option to indicate that the particular privacy campaign is alow privacy risk campaign; in response to receiving an indication ofselection of the first selection option by the one or more privacyofficers, providing, by one or more processors, the full privacy impactassessment to the user; in response to providing the full privacyassessment to the user; receiving, by one or more processors, respectiveanswers for the second plurality of question/answer pairings regardingthe one or more privacy characteristics of the particular privacycampaign; using one or more computer processors, calculating a riskscore based on the respective answers for the second plurality ofquestion/answer parings and the one or more privacy characteristics ofthe particular privacy campaign, wherein calculating the risk scorecomprises: electronically determining a weighting factor for each of thesecond plurality of question/answer parings, wherein the one or moreprivacy characteristics include: a nature of personal data associatedwith the particular privacy campaign; a physical location of thepersonal data associated with the particular privacy campaign; aphysical location of the personal data associated with the particularprivacy campaign; a number of individuals having access to the personaldata associated with the particular privacy campaign; a length of timethat the personal data associated with the particular privacy campaignwill be retained in storage; and a type of individual from which thepersonal data associated with the particular privacy campaignoriginated; and electronically determining a relative risk rating foreach of the second plurality of question/answer pairings; andelectronically calculating the risk score based upon, for eachrespective one of the second plurality of question/answer pairings, therelative risk rating, and the weighting factor; in response to receivingan indication of selection of the second selection option by the one ormore privacy officers, storing, by one or more processors, an indicationthat the particular privacy campaign is a low privacy risk campaign. 10.The computer-implemented data processing method of claim 9, wherein theprivacy risk score is determined by associating a weight factor witheach question in the first set of questions.
 11. Thecomputer-implemented data processing method of claim 10, whereinassociating a weight factor for each question in the first set ofquestions further comprises: determining that a first question in thefirst set of questions identifies a greater privacy impact than a secondquestion in the first set of questions; and assigning a weight to thefirst question in the first set of questions that is greater than aweight to be assigned to the second question in the first set ofquestions.
 12. The computer-implemented data processing method of claim9, wherein determining the privacy risk score for the particularcampaign further comprises: determining that a question in a particularquestion/answer pairing for the first plurality of question/answerpairings includes an answer, for the particular question/answer pairing,that provides a particular response; and automatically determining thatthe privacy risk score for the particular privacy campaign exceeds thethreshold privacy risk value.
 13. The computer-implemented dataprocessing method of claim 9, wherein upon receiving an indication ofselection of the first selection option by the one or more privacyofficers further comprising, the method further comprises: in responseto determining that the privacy risk score exceeds the threshold privacyrisk value, providing, by the one or more processors, the privacy impactassessment to the user that includes a second set of questions for asecond plurality of question/answer pairings that identify one or moreprivacy characteristics of the particular privacy campaign; receiving,by the one or more processors, respective answers for the secondplurality of question/answer pairings regarding the one or more privacycharacteristics of the particular privacy campaign; determining, by theone or more processors, an updated privacy risk score for the particularprivacy campaign that identifies a level of risk for one or more of theprivacy characteristics indicated in the second plurality ofquestion/answer pairings; comparing, by the one or more processors, theupdated privacy risk score to the threshold privacy risk value, thethreshold privacy risk value indicating a pre-determined level of riskregarding the one or more privacy characteristics of the particularprivacy campaign; determining, by the one or more processors, whetherthe updated privacy risk score exceeds the threshold privacy risk value;in response to determining that the privacy risk score exceeds thethreshold privacy risk value, providing, by the one or more processors,a notification to one or more privacy officers associated with theprivacy campaign that the particular privacy campaign is a high privacyrisk campaign; and in response to determining that the privacy riskscore does not exceed the threshold privacy risk value, storing, by theone or more processors, the indication that the particular privacycampaign is a low privacy risk campaign.
 14. The computer-implementeddata processing method of claim 9, wherein the threshold privacy riskvalue is configured to be set by one or more privacy officers associatedwith the privacy campaign.
 15. The computer-implemented data processingmethod of claim 14, wherein the threshold privacy risk value isconfigured to be adjusted based on a type of campaign for the particularprivacy campaign.
 16. A computer-implemented data processing method forefficiently conducting privacy risk assessments for a plurality ofprivacy campaigns, the method comprising, for each of the plurality ofprivacy campaigns: presenting, by one or more processors, a thresholdprivacy assessment to a user that includes a first set of one or morequestions for a first plurality of question/answer pairings thatidentify one or more privacy characteristics of the particular privacycampaign; receiving, by one or more processors, respective answers forthe first plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign;determining, by one or more processors, a first privacy risk score forthe particular privacy campaign that identifies a level of risk for oneor more of the privacy characteristics indicated in the first pluralityof question/answer pairings; comparing, by one or more processors, thefirst privacy risk score to a first threshold privacy risk value, thefirst threshold privacy risk value indicating a pre-determined level ofrisk regarding the one or more privacy characteristics of the particularprivacy campaign; determining, by one or more processors, that the firstprivacy risk score exceeds the first threshold privacy risk value; inresponse to determining that the first privacy risk score exceeds thefirst threshold privacy risk value, providing, by one or moreprocessors, a privacy impact assessment to the user that includes asecond set of questions for a second plurality of question/answerpairings that identify one or more privacy characteristics of theparticular privacy campaign, the second set of one or more questionsincludes a greater number of questions than the first set of one or morequestions; receiving, by one or more processors, respective answers forthe second plurality of question/answer pairings regarding the one ormore privacy characteristics of the particular privacy campaign;determining, by one or more processors, a second privacy risk score forthe particular privacy campaign that identifies a level of risk for oneor more of the privacy characteristics indicated in the second pluralityof question/answer pairings, wherein determining the second privacy riskscore comprises: identifying a weighting factor for each of the secondplurality of question/answer pairings, the second plurality ofquestion/answer pairings including: an indication of a physical storagelocation of personal data collected as part of the particular privacycampaign; and an indication of a length of time that the personal datacollected as part of the particular privacy campaign will be stored inthe physical storage location; electronically determining a relativerisk rating for each of the second plurality of question/answerpairings; electronically calculating the second privacy risk score basedupon, for each of the second plurality of question/answer parings, therelative risk rating and the weighting factor; and electronicallyassociating the second risk score with the particular privacy campaign;comparing, by one or more processors, the second privacy risk score to asecond threshold privacy risk value, the second threshold privacy riskvalue indicating a pre-determined level of risk regarding the one ormore privacy characteristics of the particular privacy campaign;determining, by one or more processors, whether the second privacy riskscore exceeds the second threshold privacy risk value; in response todetermining that the second privacy risk score exceeds the secondthreshold privacy risk value, providing, by one or more processors, anadvanced privacy impact assessment to the user that includes a third setof questions for a third plurality of question/answer pairings thatidentify one or more privacy characteristics of the particular privacycampaign, the third set of one or more questions includes a greaternumber of questions than the second set of one or more questions; and inresponse to determining that the second privacy risk score does notexceed the second threshold privacy risk value, storing, by one or moreprocessors, an indication that the particular privacy campaign is a lowprivacy risk campaign.
 17. The computer-implemented data processingmethod of claim 16, wherein the first threshold privacy risk value isdifferent from the second threshold privacy risk value.
 18. Thecomputer-implemented data processing method of claim 16, wherein thestep of determining the second privacy risk score includes incorporatingthe first privacy risk score in the determining of the second privacyrisk score.
 19. The computer-implemented data processing method of claim16, wherein in response to determining that the first privacy risk scoreexceeds the first threshold privacy risk value, the method furthercomprises: providing, by the one or more processors, a notification toone or more privacy officers associated with the privacy campaign toindicate that the first privacy risk score exceeds the first thresholdprivacy risk value.
 20. The computer-implemented data processing methodof claim 16, wherein the threshold privacy risk value is configured tobe set by one or more privacy officers associated with the privacycampaign.